How to Write a Checker

You can find some simple examples in the distribution ( and

There are three kinds of checkers:

  • Raw checkers, which analyse each module as a raw file stream.
  • Token checkers, which analyse a file using the list of tokens that represent the source code in the file.
  • AST checkers, which work on an AST representation of the module.

The AST representation is provided by the astroid library. astroid adds additional information and methods over ast in the standard library, to make tree navigation and code introspection easier.

Writing an AST Checker

Let's implement a checker to make sure that all return nodes in a function return a unique constant. Firstly we will need to fill in some required boilerplate:

import astroid

from pylint.checkers import BaseChecker
from pylint.interfaces import IAstroidChecker

class UniqueReturnChecker(BaseChecker):
    __implements__ = IAstroidChecker

    name = 'unique-returns'
    priority = -1
    msgs = {
        'W0001': (
            'Returns a non-unique constant.',
            'All constants returned in a function should be unique.'
    options = (
                'default': False, 'type': 'yn', 'metavar' : '<y_or_n>',
                'help': 'Allow returning non-unique integers',

So far we have defined the following required components of our checker:

  • A name. The name is used to generate a special configuration

    section for the checker, when options have been provided.

  • A priority. This must be to be lower than 0. The checkers are ordered by

    the priority when run, from the most negative to the most positive.

  • A message dictionary. Each checker is being used for finding problems

    in your code, the problems being displayed to the user through messages. The message dictionary should specify what messages the checker is going to emit. It has the following format:

    msgs = {
        'message-id': (
            'displayed-message', 'message-symbol', 'message-help'
    • The message-id should be a 5-digit number, prefixed with a message category. There are multiple message categories, these being C, W, E, F, R, standing for Convention, Warning, Error, Fatal and Refactoring. The rest of the 5 digits should not conflict with existing checkers and they should be consistent across the checker. For instance, the first two digits should not be different across the checker.
    • The displayed-message is used for displaying the message to the user, once it is emitted.
    • The message-symbol is an alias of the message id and it can be used wherever the message id can be used.
    • The message-help is used when calling pylint --help-msg.

We have also defined an optional component of the checker. The options list defines any user configurable options. It has the following format:

options = (
    'option-symbol': {'argparse-like-kwarg': 'value'},
  • The option-symbol is a unique name for the option. This is used on the command line and in config files. The hyphen is replaced by an underscore when used in the checker, similarly to how you would use argparse.Namespace.

Next we'll track when we enter and leave a function.

def __init__(self, linter=None):
    super(UniqueReturnChecker, self).__init__(linter)
    self._function_stack = []

def visit_functiondef(self, node):

def leave_functiondef(self, node):

In the constructor we initialise a stack to keep a list of return nodes for each function. An AST checker is a visitor, and should implement visit_<lowered class name> or leave_<lowered class name> methods for the nodes it's interested in. In this case we have implemented visit_functiondef and leave_functiondef to add a new list of return nodes for this function, and to remove the list of return nodes when we leave the function.

Finally we'll implement the check. We will define a visit_return function, which is called with a astroid.node_classes.Return node.

We'll need to be able to figure out what attributes a astroid.node_classes.Return node has available. We can use astroid.extract_node() for this:

>>> node = astroid.extract_node("return 5")
>>> node
<Return l.1 at 0x7efe62196390>
>>> help(node)
>>> node.value
< l.1 at 0x7efe62196ef0>

We could also construct a more complete example:

>>> node_a, node_b = astroid.extract_node("""
... def test():
...     if True:
...         return 5 #@
...     return 5 #@
>>> node_a.value
< l.4 at 0x7efe621a74e0>
>>> node_a.value.value
>>> node_a.value.value == node_b.value.value

For astroid.extract_node(), you can use #@ at the end of a line to choose which statements will be extracted into nodes.

For more information on astroid.extract_node(), see the astroid documentation.

Now we know how to use the astroid node, we can implement our check.

def visit_return(self, node):
    if not isinstance(node.value, astroid.node_classes.Const):

    for other_return in self._function_stack[-1]:
       if (node.value.value == other_return.value.value and
           not (self.config.ignore_ints and node.value.pytype() == int)):
               'non-unique-returns', node=node,


Once we have established that the source code has failed our check, we use add_message() to emit our failure message.

Finally, we need to register the checker with pylint. Add the register function to the top level of the file.

def register(linter):

We are now ready to debug and test our checker!

Debugging a Checker

It is very simple to get to a point where we can use pdb. We'll need a small test case. Put the following into a Python file:

def test():
    if True:
        return 5
    return 5

def test2():
    if True:
        return 1
    return 5

After inserting pdb into our checker and installing it, we can run pylint with only our checker:

$ pylint --load-plugins=my_plugin --disable=all --enable=non-unique-returns

Now we can debug our checker!


my_plugin refers to a module called This module can be made available to pylint by putting this module's parent directory in your PYTHONPATH environment variable or by adding the file to the pylint/checkers directory if running from source.

Testing a Checker

Pylint is very well suited to test driven development. You can implement the template of the checker, produce all of your test cases and check that they fail, implement the checker, then check that all of your test cases work.

Pylint provides a pylint.testutils.CheckerTestCase to make test cases very simple. We can use the example code that we used for debugging as our test cases.

import my_plugin
import pylint.testutils

class TestUniqueReturnChecker(pylint.testutils.CheckerTestCase):
    CHECKER_CLASS = my_plugin.UniqueReturnChecker

    def test_finds_non_unique_ints(self):
        func_node, return_node_a, return_node_b = astroid.extract_node("""
        def test(): #@
            if True:
                return 5 #@
            return 5 #@

        with self.assertAddsMessages(

    def test_ignores_unique_ints(self):
        func_node, return_node_a, return_node_b = astroid.extract_node("""
        def test(): #@
            if True:
                return 1 #@
            return 5 #@

        with self.assertNoMessages():

Once again we are using astroid.extract_node() to construct our test cases. pylint.testutils.CheckerTestCase has created the linter and checker for us, we simply simulate a traversal of the AST tree using the nodes that we are interested in.