“A goal is a dream with a deadline.” — Napleon Hill

Besides the configuration for Mercurial the preferred DVCS, A bug-tracking and project management tool is required to manage the timeline. Trac is my all-time favorite and it supports the Mercurial via TracMercurial plugin.

Before we move on, we need to rebuild the python-2.6 to get some missing modules with C extensions back:

Install Trac and MercurialTrac

When repository type is prompted, use hg instead.

Then we install the MercurialTrac plugin globally, so it can be used later for other projects:

Now it is time to run Trac in TracStandalone mode to verify the configuration in Trac side.

Configure Nginx to and FastCGI
The Trac instance is loaded via spawn-fcgi as other web applications using this script. The PATH is overrided to use python-2.6, and TRAC_ENV_PARENT_DIR is exported explicitly. I doubt this may contaminate other Trac instances, I will fix it later if so.

The multiple Trac instances are located in the /projects/ path, and we need HTTP Basic Auth to protect the entry point.

Any thoughts to refactor the configuration to eliminate the duplication?

As my VPS provider Advantagecom Networks gracefully acknowledged the life-time promotion I enrolled in one year ago, I decided to settle in this ISP. Which also means that I am stuck to the current configuration: python-2.3.4 in CentOS 4.

Unlike Gentoo, there is no shortcut to upgrade CentOS 4 to CentOS 5 seamlessly. Some adventurous pilots tried and failed miserably, also the customer service disregarded this approach. I wish I could reinstall the OS in SSH session. So we fallback the plan B to update the essential components only.

Update the python

Update the setuptools for python-2.6
Temporarily override the PATH to use python-2.6:

By default, easy_install will be installed into /opt/python/bin

Install Mercurial and flup

Setup the Mercurial repository

Serve Mercurial via flup
Copy the fastcgi script hgwebdir.fcgi from /usr/share/doc/mercurial-1.3.1/contrib/, and configure the hgweb.config:

Spawn the fastcgi script using this script.
Note: the PATH environment variable needs to be overrided by /opt/python/bin to use python-2.6.

Install Nginx
Just follow this HOWTO.

Now we need to setup the Nginx to expose the Mercurial repository in nginx.conf:

The directive limit_except in Nginx seem not to work as expected. If we add auth_basic in limit_except block, Nginx will ask for the credential first, then tries to server the static content in /hg/project_name instead of passing the request to the underlying fastcgi. I encountered the similar problem in MoinMoin setup, so I just deny all the POST operations, and use SSH instead. This is not the perfect solution for sure, but it works fine for personal source depot.

Though I am a die-hard RTFM guy, it never hurt to take the advantage of expertise of the peers. Django 1.0 Template Development focuses on a relatively narrow topic, the template system of Django. The author puts himself in an dilemma: he expects the target audience to have basic ideas of Django system, but still has to go over all the hassles(not really though) to kick start a new project to make the book self-contained. I think the author did a great job for a beginners, but I still highly recommend the official DjangoBook, tutorial and documentation.

After two chapters warm-up, Chapter 3 shows the magic of Context and RequestContext. It is interesting to see how the project evolve from the low-level operation to the shortcuts. Chapter 4 introduces the built-in tags in the toolbox. Chapter 5 and 6 demonstrates the template inheritance and how multiple templates are served. In chapter 7, the developers can extend their toolbox by creating new filter tags. Chapter 9 gives series examples for admin UI customization. Chapter 8 and 10 are about the performance, pagination and cache. Last but not the least, L10N in chapter 11.

The examples in each chapter is atomic for easy understanding, but in my humble opinion, most of them do not impress the readers the power of Django. The framework shines to solve BIG and complex questions. I just wonder what if the author starts a much more ambitious project with complicated specification, and later decompose it to small tasks and address them in each chapter to make the point, just like Dive into Python does.

Furthermore, I would appreciate if the author could share more first-hand experience with readers. Engineering is always about question-solving. The framework is naturally easy to learn, otherwise, why bother? But it may suck in the big time if it does not scale. Any real world case would help to establish the confidence for further acceptance.

The bottom line: a good book for beginners, some chapters are quite beefy for the topic. As Django is a fast-evolving project, I hope the author will bring more juicy examples in the future edition.

What do you think about a dict.get operation does?

Something like this?

That is my intuition, just like C’s short-circuit evaluation, the fallback is not evaluated until the requested key does not exist. Unfortunately, this not try, for example:

f is always evaluated regardless whether the key exists or not.

This is expected behavior from the compiler/interpreter perspective, the fallback value needs to be reduced first before get is invoked. It would be nice to evaluate get lazily to avoid the expensive try/except mechanism; or tedious has_key test.

In the last post, regular expression is used to fetch the specific information. To access the structured information, BeautifulSoap BeautifulSoup is preferred for its simplicity and convenient API:

• You may override the fromEncoding in the constructor, this is very useful for non-roman, non-standard web pages.
• Versatile find/findAll on tag, attributes.
• Developer-friendly syntactic sugar, the Tag implements the interface of string, list, dict and callable function, so there are many ways to access the data as you wish. The drawback of this approach is the typo is only caught in the run time instead of compilation time.
• Easy to deploy, only one BeautifulSoup.py file.

Something I don’t like:

• No XPath support, more efforts are needed to port from JavaScript.
• The API does not support stream, or file object. Laziness is always cherished for pipelining.
• Why BeautifulSoup? I have made typo as soap more than ten times.

Here is the home-brewed script to wage through the Dvbbs thread to find the corresponding messages： elevator.py