Awesome
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.
For a static analysis project to succeed, developers must feel they benefit from and enjoy using it.
For documentation and a list of rules see docs.
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: 0.10.2, mccabe: 0.5.3, pycodestyle: 2.2.0, pyflakes: 1.3.0
Note the dlint: 0.10.2
.
Using
Dlint uses flake8
to perform its linting functionality which 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 fromast.NodeVisitor
.
- If for some reason you'd like to avoid this, then you must implement
the
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/