Dlint

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

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.

• John Carmack, 2011

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

• Lessons from Building Static Analysis Tools at Google

For documentation and a list of rules see docs.

Installing

$ python -m pip install dlint

And double check that it was installed correctly:

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

...

Installed plugins: dlint: 0.16.0, mccabe: 0.5.3, pycodestyle: 2.2.0, pyflakes: 1.3.0

Note the dlint: 0.16.0.

Using

Dlint builds on flake8 to perform its linting. This provides many useful features without re-inventing the wheel.

CLI

Let's run a simple check:

$ cat << EOF > test.py
print("TEST1")
exec('print("TEST2")')
EOF

$ python test.py
TEST1
TEST2

$ python -m flake8 --select=DUO test.py
test.py:2:1: DUO105 use of "exec" is insecure

• Why is this insecure? To learn more visit /docs/linters/DUO105.md.
• Why DUO? Dlint was originally developed by the Duo Labs team.

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:

• Vim: https://github.com/vim-syntastic/syntastic
• Emacs: https://github.com/flycheck/flycheck
• Sublime: https://github.com/SublimeLinter/SublimeLinter-flake8
• PyCharm: https://foxmask.net/post/2016/02/17/pycharm-running-flake8/
• Atom: https://atom.io/packages/linter-flake8
• Visual Studio Code: https://code.visualstudio.com/docs/python/linting#_flake8

Integrating

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

For more information and examples see 'How can I integrate Dlint into XYZ?'.

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

Benchmarking

$ pytest -k test_benchmark_run --benchmark-py-file /path/to/file.py tests/test_benchmark/

Or get benchmark results for linters individually:

$ pytest -k test_benchmark_individual --benchmark-py-file /path/to/file.py tests/test_benchmark/

Or run against a single linter:

$ pytest -k test_benchmark_individual[DUO138-BadReCatastrophicUseLinter] --benchmark-py-file /path/to/file.py tests/test_benchmark/