django在一个项目的目录结构划分方面缺乏必要的规范,因此不同人的项目组织形式也千奇百怪,而且也很难说谁的做法就比较好。我根据自己的项目组织习惯,发布了一个项目dj-scaffold。
前些天在reddit上为我的项目dj-scaffold打了个“广告”(见:http://redd.it/kw5d4)。不想评价甚糟,甚至差点被打成负分。其中更也人将这个项目说的一文不值。面对负面声音虽然会有些不爽,但其中的建设性意见还是需要听取的,至于那些纯属个人偏好部分就自动过滤了。
在谈及settings文件如何组织时,coderanger建议参考The Best (and Worst) of Django中的做法。文中的主要观点是开发环境和生产环境的配置都需要放到VCS中进行版本控制。参考文中的做法,我对settings模块做了部分调整。注:代码 https://github.com/vicalloy/dj-scaffold/tree/master/dj_scaffold/conf/prj/sites/settings
local_settings的弊病
为将项目的默认配置和本地配置区分开,最常用的做法是增加一个local_settings.py文件,并在settings文件的最后对该文件进行import。
try: from local_settings import * except: pass
由此引发的问题是你不能对local_settings.py进行版本控制,部署环境的配置万一丢失将难以找回。
解决方案
针对该问题,建议的解决方案如下
合理的配置文件组织方式
| |-__init__.py
| |-base.py #默认配置信息
| |-dev.py #开发环境的配置
| |-local.sample #本地的扩展配置在dev和production的最后进行import
| |-pre.sample #设置当前使用的配置为生产环境还是开发环境
| `-production.py #生产环境的配置
使用方式
<strong>DJANGO_SETTINGS_MODULE</strong>
django的admin脚本提供了settings参数用于指定当前使用的配置文件
django-admin.py shell --settings=settings.dev
在wsgi脚本中则可直接设置需要使用的settings
deploy.wsgi os.environ['DJANGO_SETTINGS_MODULE'] = settings.production
简化参数
当然,如果每次使用django-admin.py的时候都要带上settings参数还是非常恼人,所以推荐的做法是在pre.py中配置自己所需要使用的配置文件。
SETTINGS = 'production' #dev

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

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It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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