Although your code is given a score as a percentage, that does not mean that aiming for 100% is useful or necessary. The numeric value is given to show changes up or down, rather than to provide an absolute value.
Many large codebases will have a lot of warnings issued by Landscape, and in addition, some of those warnings will not be accurate. Therefore it makes more sense to think in terms of incremental changes - if you commit code, is the overall code quality going up or down? When you create a new feature, have you added lots of new errors?
This approach helps you start by staying on top of any technical debt you have. If your codebase gets a score of 50%, that does not mean it’s time to spend a month focusing only on fixing warnings. It just means that you should pay a little extra attention so that every week your score improves and so your overall code quality improves.
Feature branches are a great development method for separating out features and bug fixes into smaller manageable chunks. It also means that, using GitHub’s Pull Requests, Landscape can check and individually comment on a particular feature.
For example, if you create a new feature in a feature branch, then create a pull request, Landscape will comment on it to inform you of changes to the number of errors and warnings introduced by the PR. This is not only helpful to see if you have added any new problems, but in general for the whole project as it breaks down the process of fixing and improving code quality into smaller manageable chunks.
You can configure this for an entire organisation via your preferences page and also override these settings per-repository on the repository settings page (small cog icon at the top-right of a repository page).
Landscape has several Django-specific behaviours which will be turned on if it detects that you are using Django. This will prevent generating warnings such as ‘MyModel has no member called objects’ and similar, which are caused by the metaprogramming Django does.
This behaviour will be turned on by default but it is possible that Landscape does not figure out that you are using Django. Dependencies are determined by parsing setup.py or requirements.txt, but if they cannot parsed, they are in a non-standard location, or if you don’t specify dependencies in your project, then you will have to manually tell Landscape to use Django plugins.
To do this, you will need a .landscape.yaml configuration file, and include the following:
uses: - django
Similarly, Landscape has Flask-specific behaviours thanks to the awesome pylint-flask plugin.