Adding a New Linter to the Tree

Linter Requirements

For a linter to be integrated into the mozilla-central tree, it needs to have:

  • Any required dependencies should be installed as part of ./mach bootstrap
  • A ./mach lint interface
  • Running ./mach lint command must pass (note, linters can be disabled for individual directories)
  • Taskcluster/Treeherder integration
  • In tree documentation (under tools/lint/docs) to give a basic summary, links and any other useful information

Linter Basics

A linter is a yaml file with a .yml extension. Depending on how the type of linter, there may be python code alongside the definition, pointed to by the ‘payload’ attribute.

Here’s a trivial example:


Now no-eval.yml gets passed into

Linter Types

There are four types of linters, though more may be added in the future.

  1. string - fails if substring is found
  2. regex - fails if regex matches
  3. external - fails if a python function returns a non-empty result list
  4. structured_log - fails if a mozlog logger emits any lint_error or lint_warning log messages

As seen from the example above, string and regex linters are very easy to create, but they should be avoided if possible. It is much better to use a context aware linter for the language you are trying to lint. For example, use eslint to lint JavaScript files, use flake8 to lint python files, etc.

Which brings us to the third and most interesting type of linter, external. External linters call an arbitrary python function which is responsible for not only running the linter, but ensuring the results are structured properly. For example, an external type could shell out to a 3rd party linter, collect the output and format it into a list of ResultContainer objects. The signature for this python function is lint(files, config, **kwargs), where files is a list of files to lint and config is the linter definition defined in the .yml file.

Structured log linters are much like external linters, but suitable for cases where the linter code is using mozlog and emits lint_error or lint_warning logging messages when the lint fails. This is recommended for writing novel gecko-specific lints. In this case the signature for lint functions is lint(files, config, logger, **kwargs).

Linter Definition

Each .yml file must have at least one linter defined in it. Here are the supported keys:

  • description - A brief description of the linter’s purpose (required)
  • type - One of ‘string’, ‘regex’ or ‘external’ (required)
  • payload - The actual linting logic, depends on the type (required)
  • include - A list of glob patterns that must be matched (optional)
  • exclude - A list of glob patterns that must not be matched (optional)
  • extensions - A list of file extensions to be considered (optional)
  • setup - A function that sets up external dependencies (optional)
  • support-files - A list of glob patterns matching configuration files (optional)

In addition to the above, some .yml files correspond to a single lint rule. For these, the following additional keys may be specified:

  • message - A string to print on infraction (optional)
  • hint - A string with a clue on how to fix the infraction (optional)
  • rule - An id string for the lint rule (optional)
  • level - The severity of the infraction, either ‘error’ or ‘warning’ (optional)

For structured_log lints the following additional keys apply:

  • logger - A StructuredLog object to use for logging. If not supplied one will be created (optional)


Here is an example of an external linter that shells out to the python flake8 linter, let’s call the file

import json
import os
import subprocess
from collections import defaultdict

from mozlint import result

Could not find flake8! Install flake8 and try again.

def lint(files, config, **lintargs):
    import which

    binary = os.environ.get('FLAKE8')
    if not binary:
            binary = which.which('flake8')
        except which.WhichError:
            return 1

    # Flake8 allows passing in a custom format string. We use
    # this to help mold the default flake8 format into what
    # mozlint's ResultContainer object expects.
    cmdargs = [
    ] + files

    proc = subprocess.Popen(cmdargs, stdout=subprocess.PIPE, env=os.environ)
    output = proc.communicate()[0]

    # all passed
    if not output:
        return []

    results = []
    for line in output.splitlines():
        # res is a dict of the form specified by --format above
        res = json.loads(line)

        # parse level out of the id string
        if 'code' in res and res['code'].startswith('W'):
            res['level'] = 'warning'

        # result.from_linter is a convenience method that
        # creates a ResultContainer using a LINTER definition
        # to populate some defaults.
        results.append(result.from_config(config, **res))

    return results

Now here is the linter definition that would call it:

    description: Python linter
        - '**/*.py'
    type: external
    payload: py.flake8:lint
        - '**/.flake8'

Notice the payload has two parts, delimited by ‘:’. The first is the module path, which mozlint will attempt to import. The second is the object path within that module (e.g, the name of a function to call). It is up to consumers of mozlint to ensure the module is in sys.path. Structured log linters use the same import mechanism.

The support-files key is used to list configuration files or files related to the running of the linter itself. If using --outgoing or --workdir and one of these files was modified, the entire tree will be linted instead of just the modified files.

Bootstrapping Dependencies

Many linters, especially 3rd party ones, will require a set of dependencies. It could be as simple as installing a binary from a package manager, or as complicated as pulling a whole graph of tools, plugins and their dependencies.

Either way, to reduce the burden on users, linters should strive to provide automated bootstrapping of all their dependencies. To help with this, mozlint allows linters to define a setup config, which has the same path object format as an external payload. For example:

    description: Python linter
        - '**/*.py'
    type: external
    payload: py.flake8:lint
    setup: py.flake8:setup

The setup function takes a single argument, the root of the repository being linted. In the case of flake8, it might look like:

import subprocess
from distutils.spawn import find_executable

def setup(root):
    if not find_executable('flake8'):['pip', 'install', 'flake8'])

The setup function will be called implicitly before running the linter. This means it should return fast and not produce any output if there is no setup to be performed.

The setup functions can also be called explicitly by running mach lint --setup. This will only perform setup and not perform any linting. It is mainly useful for other tools like mach bootstrap to call into.