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Dlint is a tool for encouraging best coding practices and helping ensure we're writing secure Python code.

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Dlint

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Dlint is a tool for encouraging best coding practices and helping ensure we're writing secure Python code.

The most important thing I have done as a programmer in recent years is to aggressively pursue static code analysis. Even more valuable than the hundreds of serious bugs I have prevented with it is the change in mindset about the way I view software reliability and code quality.

For a static analysis project to succeed, developers must feel they benefit from and enjoy using it.

Installing

$ python -m pip install dlint

Specify python2 or python3 to install for a specific Python version.

And double check that it was installed correctly:

$ python -m flake8 -h
Usage: flake8 [options] file file ...

...

Installed plugins: dlint: 0.6.0, mccabe: 0.5.3, pycodestyle: 2.2.0, pyflakes: 1.3.0

Note the dlint: 0.6.0.

Using

Dlint uses flake8 to perform its linting functionality. This allows us to utilize many useful flake8 features without re-inventing the wheel.

CLI

Let's run a simple check:

$ cat test.py
#!/usr/bin/env python

print("TEST1")

exec('print("TEST2")')
$ python -m flake8 --select=DUO test.py
test.py:5:1: DUO105 use of "exec" not allowed

The --select=DUO flag tells flake8 to only run Dlint lint rules.

From here, we can easily run Dlint against a directory of Python code:

$ python -m flake8 --select=DUO /path/to/code

To fine-tune your linting, check out the flake8 help:

$ python -m flake8 --help

Inline Editor

Dlint results can also be included inline in your editor for fast feedback. This typically requires an editor plugin or extension. Here are some starting points for common editors:

Integrating

Dlint can easily be integrated into CI pipelines, or anything really.

TravisCI

Include Dlint in your .travis.yml configuration file:

language: python
install:
    - python -m pip install dlint
script:
    - python -m flake8 --select=DUO /path/to/code

CircleCI

Include Dlint in your .circleci/config.yml configuration file:

version: 2
jobs:
    build:
        docker:
            - image: circleci/python
        steps:
            - checkout
            - run: python -m pip install dlint
            - run: python -m flake8 --select=DUO /path/to/code

Gitlab

Include Dlint in your .gitlab-ci.yml configuration file:

stages:
    - test
test:
    image: python
    before_script:
        - python -m pip install dlint
    script:
        - python -m flake8 --select=DUO /path/to/code

Phabricator

Include Dlint in your Arcanist linting process via the .arclint configuration file:

{
    "linters": {
        "sample": {
            "type": "flake8"
        }
    }
}

Dlint rules will automatically be run via flake8 once it's installed, so the standard flake8 configuration will work. You can also utilize more granular control over the linting process:

{
    "linters": {
        "sample": {
            "type": "flake8"
        },
        "bin": ["python2.7", "python2"],
        "flags": ["-m", "flake8", "--select", "DUO"]
    }
}

Custom Plugins

Dlint's custom plugins are built on a simple naming convention, and rely on Python modules. To make a Dlint custom plugin use the following conventions:

  • The Python module name must start with dlint_plugin_.
  • The linter class name must start with Dlint.
  • The linter class should inherit from dlint.linters.base.BaseLinter.
    • If for some reason you'd like to avoid this, then you must implement the get_results function appropriately and inherit from ast.NodeVisitor.

See an example plugin for further details.

Developing

First, install development packages:

$ python -m pip install -r requirements.txt
$ python -m pip install -r requirements-dev.txt
$ python -m pip install -e .

Testing

$ pytest

Linting

$ flake8

Coverage

$ pytest --cov

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