Is there a "Large Scale Python Software Design" ?
gmuller at worldonline.nl
Tue Oct 19 19:33:03 CEST 2004
"Jonathan Ellis" <jbellis at gmail.com> schreef in bericht
news:1098195361.960550.257070 at z14g2000cwz.googlegroups.com...
> Almost four years ago I started working at a company with about 500
> kloc of Java code. Thanks largely to tool support I was able to get in
> and start fixing bugs my first day (this is without significant prior
> Java experience). A more-experienced co-worker pointed me in the right
> direction, and the IDE did the rest. ("Find definition," "Find
> references.") Grep can do much the same thing, but painfully slowly --
> and inaccurately, when you have a bunch of interfaces implementing the
> same method names. Even after years in the codebase, I still used
> these heavily; the codebase grew to about 800 kloc during the 3 years I
> worked there. Developers came and went; even if my memory were good
> enough to remember all the code _I_ ever wrote, I'd still have to
> periodically repeat the familiarization process with code written by
The point you make is that good tooling is important. I worked 12 years ago
in a large Objective-C environment. The same static versus dynamic wars were
raging at that time (Objective-C vs C++). I fully agree that good toold make
quite a difference. Most often very simple tools can do wonders. The dynamic
nature of Objective-C made also dynamic tools feasible, with an amazing
small extension. The run-time instrumentation proved at least as powerful,
as the compile time tools. Nowadays the same code is ported to Java, but
unfortunately the same powerful instrumentation is lost.
Contrary to your believe I would jump into larger scale Python development
without hesistation. However, I would introduce a few naming conventions to
support the static tool part.
kind regards, Gerrit
Praktijk voor Psychosociale therapie Lia Charité
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