Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/dlint-py/dlint

Dlint is a tool for encouraging best coding practices and helping ensure Python code is secure.
https://github.com/dlint-py/dlint

dlint flake8 linter python security static-analysis

Last synced: 3 months ago
JSON representation

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

Awesome Lists containing this project

README 

        
# Dlint



[![CI](https://github.com/dlint-py/dlint/actions/workflows/ci.yml/badge.svg?branch=master)](https://github.com/dlint-py/dlint/actions/workflows/ci.yml)

[![Coverage Status](https://coveralls.io/repos/github/dlint-py/dlint/badge.svg?branch=master)](https://coveralls.io/github/dlint-py/dlint?branch=master)

[![Python Versions](https://img.shields.io/pypi/pyversions/dlint.svg)](https://pypi.org/project/dlint/)

[![PyPI Version](https://img.shields.io/pypi/v/dlint.svg)](https://pypi.org/project/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](https://www.gamasutra.com/view/news/128836/InDepth_Static_Code_Analysis.php)



> 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](https://cacm.acm.org/magazines/2018/4/226371-lessons-from-building-static-analysis-tools-at-google/fulltext)



For documentation and a list of rules see [docs](https://github.com/dlint-py/dlint/tree/master/docs).



# Installing



```bash

$ python -m pip install dlint

```



And double check that it was installed correctly:



```bash

$ python -m flake8 -h

Usage: flake8 [options] file file ...



...



Installed plugins: dlint: 0.15.0, mccabe: 0.5.3, pycodestyle: 2.2.0, pyflakes: 1.3.0

```



Note the `dlint: 0.15.0`.



# 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:



```bash

$ cat << EOF > test.py

print("TEST1")

exec('print("TEST2")')

EOF

```



```bash

$ python test.py

TEST1

TEST2

```



```bash

$ 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`](https://github.com/dlint-py/dlint/blob/master/docs/linters/DUO105.md)._

- _Why `DUO`? Dlint was originally developed by the [Duo Labs](https://duo.com/blog/introducing-dlint-robust-static-analysis-for-python) 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:



```bash

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

```



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



```bash

$ 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](https://github.com/vim-syntastic/syntastic)

- Emacs: [https://github.com/flycheck/flycheck](https://github.com/flycheck/flycheck)

- Sublime: [https://github.com/SublimeLinter/SublimeLinter-flake8](https://github.com/SublimeLinter/SublimeLinter-flake8)

- PyCharm: [https://foxmask.net/post/2016/02/17/pycharm-running-flake8/](https://foxmask.net/post/2016/02/17/pycharm-running-flake8/)

- Atom: [https://atom.io/packages/linter-flake8](https://atom.io/packages/linter-flake8)

- Visual Studio Code: [https://code.visualstudio.com/docs/python/linting#\_flake8](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?'](https://github.com/dlint-py/dlint/tree/master/docs#how-can-i-integrate-dlint-into-xyz).



# Custom Plugins



Dlint's custom plugins are built on a [simple naming convention](https://packaging.python.org/guides/creating-and-discovering-plugins/#using-naming-convention),

and rely on [Python modules](https://docs.python.org/3/distutils/examples.html#pure-python-distribution-by-module).

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](https://github.com/dlint-py/dlint-plugin-example) for further details.



# Developing



First, install development packages:



```bash

$ python -m pip install -r requirements.txt

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

$ python -m pip install -e .

```



## Testing



```bash

$ pytest

```



## Linting



```bash

$ flake8

```



## Coverage



```bash

$ pytest --cov

```



## Benchmarking



```bash

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

```



Or get benchmark results for linters individually:



```bash

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

```



Or run against a single linter:



```bash

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

```