A more high-level view is that as a business, as a team we want to deliver value fast. This is harder: which value to what audience are we serving? If we deliver buggy code to the client, no one is happy. If we make some users happy but our core audience is not served, then we haven't really delivered on our goals. Our goal as professionals, as entrepreneurs, is to find/create an audience, and serve that audience by giving them value.
In practice, "clean" code helps us work fast and also deliver value to our audience. Clean in this case meaning free of bugs, clearly designed, and of a design which directly meets the needs of our audience.
Automated workflow tools can help us move forward. They run very quickly, giving us positive feedback that what we write is legible and missing the most egregious errors. The basic categories of tools are 1) surface-level syntax, 2) language-centric analysis, 3) project-based unit and other tests.
For a recent project, this is our top-level Makefile. It lets us as developers get rapid feedback on the quality of our project. Also, having a single file lets these tasks be repeatable by a Continuous Integration system, so we can be confident things don't break if we had too much coffee and committed something without running tests.
all:
auto-fix:
git ls-files '*.py' \
| xargs autopep8 --in-place --aggressive
lint:
flake8
clean:
find . -name '*.pyc' | xargs rm
run:
cd cj ; ./manage.py run
test:
pytest
