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Python bindings to the Tree-sitter parsing library

Project description

Python Tree-sitter

CI pypi docs

This module provides Python bindings to the tree-sitter parsing library.

Installation

The package has no library dependencies and provides pre-compiled wheels for all major platforms.

[!NOTE] If your platform is not currently supported, please submit an issue on GitHub.

pip install tree-sitter

Usage

Setup

Install languages

Tree-sitter language implementations also provide pre-compiled binary wheels. Let's take Python as an example.

pip install tree-sitter-python

Then, you can load it as a Language object:

import tree_sitter_python as tspython
from tree_sitter import Language, Parser

PY_LANGUAGE = Language(tspython.language())

Basic parsing

Create a Parser and configure it to use a language:

parser = Parser(PY_LANGUAGE)

Parse some source code:

tree = parser.parse(
    bytes(
        """
def foo():
    if bar:
        baz()
""",
        "utf8"
    )
)

If you have your source code in some data structure other than a bytes object, you can pass a "read" callable to the parse function.

The read callable can use either the byte offset or point tuple to read from buffer and return source code as bytes object. An empty bytes object or None terminates parsing for that line. The bytes must be encoded as UTF-8 or UTF-16.

For example, to use the byte offset with UTF-8 encoding:

src = bytes(
    """
def foo():
    if bar:
        baz()
""",
    "utf8",
)


def read_callable_byte_offset(byte_offset, point):
    return src[byte_offset : byte_offset + 1]


tree = parser.parse(read_callable_byte_offset, encoding="utf8")

And to use the point:

src_lines = ["\n", "def foo():\n", "    if bar:\n", "        baz()\n"]


def read_callable_point(byte_offset, point):
    row, column = point
    if row >= len(src_lines) or column >= len(src_lines[row]):
        return None
    return src_lines[row][column:].encode("utf8")


tree = parser.parse(read_callable_point, encoding="utf8")

Inspect the resulting Tree:

root_node = tree.root_node
assert root_node.type == 'module'
assert root_node.start_point == (1, 0)
assert root_node.end_point == (4, 0)

function_node = root_node.children[0]
assert function_node.type == 'function_definition'
assert function_node.child_by_field_name('name').type == 'identifier'

function_name_node = function_node.children[1]
assert function_name_node.type == 'identifier'
assert function_name_node.start_point == (1, 4)
assert function_name_node.end_point == (1, 7)

function_body_node = function_node.child_by_field_name("body")

if_statement_node = function_body_node.child(0)
assert if_statement_node.type == "if_statement"

function_call_node = if_statement_node.child_by_field_name("consequence").child(0).child(0)
assert function_call_node.type == "call"

function_call_name_node = function_call_node.child_by_field_name("function")
assert function_call_name_node.type == "identifier"

function_call_args_node = function_call_node.child_by_field_name("arguments")
assert function_call_args_node.type == "argument_list"


assert str(root_node) == (
    "(module "
        "(function_definition "
            "name: (identifier) "
            "parameters: (parameters) "
            "body: (block "
                "(if_statement "
                    "condition: (identifier) "
                    "consequence: (block "
                        "(expression_statement (call "
                            "function: (identifier) "
                            "arguments: (argument_list))))))))"
)

Or, to use the byte offset with UTF-16 encoding:

parser.language = JAVASCRIPT
source_code = bytes("'😎' && '🐍'", "utf16")

def read(byte_position, _):
    return source_code[byte_position: byte_position + 2]

tree = parser.parse(read, encoding="utf16")
root_node = tree.root_node
statement_node = root_node.children[0]
binary_node = statement_node.children[0]
snake_node = binary_node.children[2]
snake = source_code[snake_node.start_byte:snake_node.end_byte]

assert binary_node.type == "binary_expression"
assert snake_node.type == "string"
assert snake.decode("utf16") == "'🐍'"

Walking syntax trees

If you need to traverse a large number of nodes efficiently, you can use a TreeCursor:

cursor = tree.walk()

assert cursor.node.type == "module"

assert cursor.goto_first_child()
assert cursor.node.type == "function_definition"

assert cursor.goto_first_child()
assert cursor.node.type == "def"

# Returns `False` because the `def` node has no children
assert not cursor.goto_first_child()

assert cursor.goto_next_sibling()
assert cursor.node.type == "identifier"

assert cursor.goto_next_sibling()
assert cursor.node.type == "parameters"

assert cursor.goto_parent()
assert cursor.node.type == "function_definition"

[!IMPORTANT] Keep in mind that the cursor can only walk into children of the node that it started from.

See examples/walk_tree.py for a complete example of iterating over every node in a tree.

Editing

When a source file is edited, you can edit the syntax tree to keep it in sync with the source:

new_src = src[:5] + src[5 : 5 + 2].upper() + src[5 + 2 :]

tree.edit(
    start_byte=5,
    old_end_byte=5,
    new_end_byte=5 + 2,
    start_point=(0, 5),
    old_end_point=(0, 5),
    new_end_point=(0, 5 + 2),
)

Then, when you're ready to incorporate the changes into a new syntax tree, you can call Parser.parse again, but pass in the old tree:

new_tree = parser.parse(new_src, tree)

This will run much faster than if you were parsing from scratch.

The Tree.changed_ranges method can be called on the old tree to return the list of ranges whose syntactic structure has been changed:

for changed_range in tree.changed_ranges(new_tree):
    print("Changed range:")
    print(f"  Start point {changed_range.start_point}")
    print(f"  Start byte {changed_range.start_byte}")
    print(f"  End point {changed_range.end_point}")
    print(f"  End byte {changed_range.end_byte}")

Pattern-matching

You can search for patterns in a syntax tree using a tree query:

query = PY_LANGUAGE.query(
    """
(function_definition
  name: (identifier) @function.def
  body: (block) @function.block)

(call
  function: (identifier) @function.call
  arguments: (argument_list) @function.args)
"""
)

Captures

captures = query.captures(tree.root_node)
assert len(captures) == 4
assert captures["function.def"][0] == function_name_node
assert captures["function.block"][0] == function_body_node
assert captures["function.call"][0] == function_call_name_node
assert captures["function.args"][0] == function_call_args_node

Matches

matches = query.matches(tree.root_node)
assert len(matches) == 2

# first match
assert matches[0][1]["function.def"] == [function_name_node]
assert matches[0][1]["function.block"] == [function_body_node]

# second match
assert matches[1][1]["function.call"] == [function_call_name_node]
assert matches[1][1]["function.args"] == [function_call_args_node]

The difference between the two methods is that Query.matches() groups captures into matches, which is much more useful when your captures within a query relate to each other.

To try out and explore the code referenced in this README, check out examples/usage.py.

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Algorithm Hash digest
SHA256 95bb56f5ff20fe6cfc9580dfa4497d3c9ee9dd37dbc683d3b853323c19acd130
MD5 f4d9295779ada95b0966af27015d9946
BLAKE2b-256 68853169006cfce9fe99b271a370eb2a83daa0f64ac3d2d7afb4bd4cee1d8968

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SHA256 af768b0c70b0ce53a725135c7f6e36745a964d4e2e8adb20bdc7211756a6aae6
MD5 af29c33ceecef6d30e4b837b7ad7d7d0
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SHA256 ac46271c93a811c56897fbe3bb2dfccdb487045ca0f26d38cb9ef4fdbeabedf2
MD5 6d7e2b09643d2c5ae97d5497efc5671c
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SHA256 080ffaf8df305925a7ea792bd9b9e71729ea85f3bf97d9a2efde4e44bad989a9
MD5 99b5b289c2fc5b17ced6fcfeb2a1cb85
BLAKE2b-256 39758272ab2b02b7266c9518762482c4f0a99a02c068d53130fde864c04acaf4

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SHA256 5cfe4f4682f0d21298a685f22b4a539b513311cb4d7bf3e64c66f0fe6034db49
MD5 4e509cde87652775711dde31db908486
BLAKE2b-256 07736ad67affb0b769411387ef71033175044045e05cc79a8c5c252b48c5db98

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Algorithm Hash digest
SHA256 b64bf264bc2381aaed97982e53dd7b2071e86c1e35be47aff80bbcdbd933434a
MD5 2599b271f7fda513ac392da48153425c
BLAKE2b-256 0727d629eab59dc65ce24fbf64b74cd0399c0bd2c42c856e8e93d52c87e9f500

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Algorithm Hash digest
SHA256 2196816e80f8b280b2a2f9084329153175a95f229104a9f0e534efbe601d5a9f
MD5 18245d985b66c3fb50a8eb7c1650825a
BLAKE2b-256 8c94eef80fdb8d137ef740508a0c6ae7c9a8af7e39a8d1cb666a75768605f6cb

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Algorithm Hash digest
SHA256 c95581fbd111a793cd2b12af261abd5f291a16b1e43a4abc3011d206c126bd19
MD5 ba7f2d61faf7e392122f25804be6771b
BLAKE2b-256 9c72d7ef26bea37239a739507e32381fea0071633771308f448b2d17ff9229ef

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Algorithm Hash digest
SHA256 8a027435291336db0fd10ddcb6b38952c278533cb659500ac134fbd5edc8564d
MD5 5d701f1ea7f5b18b672d2d456801136d
BLAKE2b-256 6cf2e56280349740763ee8a4114c48d9de2ba688fc1bebfc0d3db3e83b2ef991

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SHA256 a7805207eebd4b877713708d3a684b1b619bdd9da794348a668be2e126aeb1e4
MD5 63a240b924f7e9f191b251c2df68c9ea
BLAKE2b-256 c48e9a0fa47fdd1aea7ee0ed93dd504a0c6cc377c00d9951097260653ef0fe5a

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SHA256 92b9da86047bc0bba8571042f1f2e89d28968f840ad5bb431dc7bc412d06b634
MD5 ce29ff72341f32a5cd505625a3b12d9a
BLAKE2b-256 7fc1ae9e9154398d09aadd49bfcbd9147722be858b8ae8409c4451394d35df0f

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SHA256 75268cf478544ed2adb19aa85fed8832cd7c94792bd6010ac5919a86e0c1872b
MD5 570c380a43f0d0b850fc25ba79a53a86
BLAKE2b-256 9d89c366ed62a2c3c1684b1aa1dcac5a0ec2f4a6772d91842dd016ea9acf7c79

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SHA256 00555c016e5deae8befec12a01797fb06954435e48bfc707fc250c71c12d5780
MD5 63ab738133270440b97e0cd3ab5a63f2
BLAKE2b-256 aa387f73979903b3e5dbd6eca046a5b9965366f0f6ec6fd3a862e00e1f0da1ad

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SHA256 ade4f2c083286d50ecf79eb97d89a185e43e370a5b27f7c160080014ebb2aabe
MD5 4273851261442a7acdd2778bf1d07f16
BLAKE2b-256 06a0809ba2818b9e4a67435d618080da2cf362e848dbb5b9c5777cee7cc1bbaf

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Algorithm Hash digest
SHA256 7386b510c55cae43961532df8ddb8478b365b8cbc4486082bca0a6b0eb49d717
MD5 859ae0624b71d686dcf5605631cb96dd
BLAKE2b-256 42b582f772fcc0fb38f488c81566abb041f645fc44c00f595189dcd96f10782b

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Algorithm Hash digest
SHA256 560ed2eb122b9cef12ec4b9f9eec555976ed75ce9347e95286c56e0ef2a66d8f
MD5 61250b80059e88f00b227750d2d7b227
BLAKE2b-256 a2d0bfb2a7443674c32e95b81103d76c02d7ef9801b24f9fc6c80e6d90ec25fe

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Algorithm Hash digest
SHA256 82c2a873654ba771bbbff6067af090e36453fac0e4bfeff80dc3bd803d2a1dc8
MD5 81732ee2d90a9d4f1ec35a4f9ac08f0d
BLAKE2b-256 30ec4048be36558c5a31499dc923355e33f04a461a3eb2264e930d428efec73e

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SHA256 81ae139e032a0e1dd450affb8cc299e3d2e948614b970aad15e7704a532e8bcd
MD5 13ab4d65e76bdbdfc9301a6d04620ac1
BLAKE2b-256 53b99b3f4d24d2678a7f5a02d45cec22c10334d8d5753b3201a9e998c857b6d1

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Algorithm Hash digest
SHA256 0dc96f9e012759a4bfb1037b728f2faed759e125892eb9183ad120b05e4b90ec
MD5 4cb65df754b20ac356d8bfcd5c8114f0
BLAKE2b-256 66474ccd06ee7cfe54f54858d308dcb1984254340fc24147354bac0d2e23dac1

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Algorithm Hash digest
SHA256 3fc7b3d9d9d5bf1a481adf0be3254c344543329458bfc33ea788a38180df3da5
MD5 6017682578a83f45191a17655e3be3df
BLAKE2b-256 3c48ceaa6d22937316e079e2c1ec3593d1092ad8b886c6ebfdd292597b826e41

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SHA256 73efbec420083c368ccba9d3f153678fdc174e5765283c274ec1ca599c2a469d
MD5 b43a53da44a39d29932df533c5e57b85
BLAKE2b-256 e30a2cca0fbacce34e0dc10397ba431d720f4861916019d00f497c59f5e51c36

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SHA256 801845257c3718b01b4e1d58fd344cdc3f54d1b346b6754ad9f962e2401eec3b
MD5 e35bcfd0729732be6c1160f8c4485f74
BLAKE2b-256 cc3e5dcc9957825d12b3269985beba0eeaeb9a8dec94b8f5240397e5491e9383

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SHA256 8240cfcf52575267ac9509ca199c012a0adcde61b431f17730f48a52aa95741f
MD5 5ae2ec07602f5901472ccb23682d4125
BLAKE2b-256 186874f849ac246f61b68e31ff5921bdc0861484499d4c70065f68ba34976c7c

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Algorithm Hash digest
SHA256 68474230c30bad92f8cdde4744b65b0e6266926b28101537a74355787458b076
MD5 14460d86d670e35196263facc88f7386
BLAKE2b-256 2d07695e450c74df55b7bcbd04d8d4316ea5dfe2710d1c31c011952b69808fe4

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Algorithm Hash digest
SHA256 5a7311a14f98c50836559ad9ba706397261d3a4e74a5c4c3cf6684ae00551899
MD5 33f7682d6057850741729d64827a18ca
BLAKE2b-256 a3a7eaa50b390247751eb329eace0c67b8d15462a0ad237ac652dbd67440b1d8

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SHA256 19c5cf5ea2ad1a34510dc1bcfa064e4e9ad1e097ba3af7d8bc95377669d28aed
MD5 7a4d2ae77dff3316d2227c669a642fb6
BLAKE2b-256 09348ecefa14dcd86b64c1bcf66a352f12ec0c5f8576e6bf8cc13e097ac50515

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