pylons（包括TurboGears）实战笔记

pylons（包括TurboGears）实战笔记

2011-1-5 星期三 阴天

Why Pylons

Small and Simple enough! Well documentation! Easy to migrate to TurboGear and, yes, Rails.

How

发现TurboGears的文档非常给力，基本上给出了从零搭建一个网站(一个TurboGears Project)的过程，而由于pylons和TG都是使用Paster，所以基本是一样的（至少在构建步骤和配置文件上）。
Quickstarting a TurboGears 2 project(http://www.turbogears.org/2.0/docs/main/QuickStart.html)

具体如下：

0. 创建一个虚拟环境（推荐）

1. 创建项目结构——类似于antx gen

对于TG：

$paster quickstart

The paster quickstart command will create a basic project directory for you to use to get started on your TurboGears 2 application.
对于pylons：
Create a new project named HelloWorld with the following command:

$ paster create -t pylons HelloWorld

对于pylons，可以使用--list-templates查看可选的模板 $paster create --list-templates Available templates: basic_package: A basic setuptools-enabled package paste_deploy: A web application deployed through paste.deploy pylons: Pylons application template pylons_minimal: Pylons minimal application template

2. 引入项目需要的依赖——类似于antx或者maven

2.1 配置文件：对于pylons和TG，都是setup.py。（类似于antx的project.xml或者maven的pom.xml）

The setup.py and setup.cfg files control various aspects of how your Pylons application is packaged when you distribute it. They also contain metadata about the project. 
The setup.py file has a section which explicitly declares the dependencies of your application. The quickstart template has a few built in dependencies, and as you add new python libraries to your application's stack, you'll want to add them here too.

例如，如果你要使用FormBuild这个模块，那么可以在setup.py中作如下配置：
You should also add it as a dependency to your project by editing the setup.py file and adding FormBuild to the end of the install_requires argument：

install_requires=[
    "Pylons>=0.9.7",
    "SQLAlchemy>=0.5,<=0.5.99",
    "Mako",
    "FormBuild>=2.0,<2.99",
],

你当然可以直接使用 $easy_install "SQLAlchemy>=0.5,<=0.5.99" 安装，但是不如同一个依赖管理，一键搭建轻松

2.2 安装依赖包：

对于pylons和TG都是一样的命令：
Then in order to make sure all those dependencies are installed you will want to run（Set up your project in development mode by entering this command）:

$python setup.py develop

paster会根据里面的依赖配置，执行类似如下命令： $easy_install "SQLAlchemy>=0.5,<=0.5.99"

3. 初始化web应用环境——给每个模块（依赖）一个执行初始化的时机（如SQLAlchemy），其实会执行每个module下的_init.py文件，如model/init.py_。

python module The model directory contains an _init_.py file which makes that directory name into a python module (so you can use the Python expression import model).

说明：这一步往往需要执行多次，每次做了什么修改，如数据模型修改，都可以跑一下。

Another key piece of TG2 application setup infrastructure is the paster setup-appcommand which takes a configuration file and runs websetup.py in that context. This allows you to use websetup.py to create database tables, pre-populate require data into your database, and otherwise make things nice for people fist setting up your app.
Note If it's the first time you're going to use the application, and you told quickstart to include authentication+authorizaiton, you will have to run setup-app to set it up (e.g., create a test database):

$paster setup-app development.ini

websetup.py
The websetup.py contains any code that should be executed when an end user has installed your Pylons application and needs to initialize it. It frequently contains code to create the database tables required by your application, for example.
If this is the first time you're starting the application you have to run the following command to create and initialize your test database:

$paster setup-app development.ini

This will create the database using the information stored in the development.ini file which by default makes single file SQLite database in the local file system. In addition to creating the database, it runs whatever extra database loaders or other setup are defined in websetup.py. In a quickstarted project with Auth enabled it creates a couple of basic users, groups, and permissions for you to use as an example.

It also shows how you can add new data automatically to the database when you need to add bootstrap data of your own.

4. 启动服务器

At this point your project should be operational, and you're ready to start up the app. To start a TurboGears 2 app, cd to the new directory (helloworld) and issue command paster serve to serve your new application:

$paster serve development.ini

As soon as that's done point your browser at http://localhost:8080/ and you'll see a nice welcome page with the inform(flash) message and current time.

By default the paster serve command is not in auto-reload mode as the CherryPy server used to be. If you also want your application to auto-reload whenever you change a source code file just add the --reload option to paster serve: $paster serve --reload development.ini

You can easily edit development.ini to change the default server port used by the built-in web server: [server:main] ... port = 8080

至此，你的项目骨架已经搭建起来了。接下来的工作就是所谓MVC构建了。

5. MVC构建

下面的顺序是随机的，大家根据自己的习惯开发。一般来说，Domain Driven Development会从model开始开发，Page Driven Development会从view开始开发。笔者是属于后台开发人员，所以一般选择前者。

5.1 创建model

现在几乎所有的动态语言web框架都采用了某种ORM框架，在python的世界里，sqlalchemy是最受欢迎和推荐的。这里也只介绍这个框架。

Once you have configured the engine, it is time to configure the model. This is easy to do; you simply add all your classes, tables, and mappers to the end of model/_init_.py.

5.1 创建Controller：

$paster controller controllerName

对于TG：
貌似没有构建骨架的命令，不过我怀疑是跟pylons一样的。

5.2 创建view

6. 分层架构＆模块化

这个根据具体业务需求决定了。不过在使用了ORM的动态语言web框架中，DAO与Model（DO/DTO）是紧密结合的。所以可能没有单独的所谓的DAL层了。

7. 总结

回过头来再看一下pylons和TG的搭建过程，有J2EE经验的同学会惊讶的发现其实跟使用maven或者ant构建工具的Java web项目搭建过程是如此惊人的一致。另外，一些思想，如viewHelper，在一些框架中也能经常见到。

杂七杂八

You can access your models from within the python/ipython shell by typing: $paster shell development.ini from your root directory. If ipython is installed within your virtual environment, it will be the default python shell.

一些补充资料

SQLAlchemy

观于sqlalchemy的介绍，SQLAlchemy 0.5.8 官方文档 (http://www.sqlalchemy.org/docs/05/reference/sqlalchemy/index.html)和pylonsbook(http://pylonsbook.com/en/1.1/introducing-the-model-and-sqlalchemy.html)的介绍比较给力。特别是后者，一个介绍web框架的文档，能从一个独立使用sqlalchemy的角度做了深入浅出的介绍，非常难得。

SQLAlchemy架构

其中 The abstraction layer consists of the SQL Expression API and the Metadata and Type APIs, which help isolate your Python code from the details of the underlying database engine.

使用Engine API链接数据库进行操作

The lowest-level API you are likely to use is the Engine API. This represents a low-level abstraction of a database engine, allowing you to use the same API to create connections to different RDBMSs for sending SQL statements and for retrieving results.

engine_test.py

from sqlalchemy.engine import create_engine

engine = create_engine('sqlite:///:memory:')
connection = engine.connect()
connection.execute(
            """
            CREATE TABLE users (
                    username VARCHAR PRIMARY KEY,
                    password VARCHAR NOT NULL
            );
            """
)
connection.execute(
            """
            INSERT INTO users (username, password) VALUES (?, ?);
            """,
            "foo", "bar"
)

result = connection.execute("select username from users")

for row in result:
    print "username:", row['username']

connection.close()

To work with an engine, you need to have a connection to it. The connection in the example is an instance of a SQLAlchemy Connection object, and result is a SQLAlchemy ResultProxy object (very much like a DB-API cursor) that allows you to iterate over the results of the statement you have executed.
运行这个脚本，得到如下输出：

(env)forrest@ubuntu:~/Install/virtualenv-1.4.5/env/SimpleSite/simplesite/model$ python engine_test.py 
username: foo

When using create_engine(), you can specify different data source names (DSNs) to connect to different databases. For example, with SQLite, you can use sqlite:///relative/path to specify a file relative to the current working directory. You can use sqlite:////absolute/path to specify an absolute path. SQLite also has a memory mode that doesn't use the filesystem at all and loses all its information when the program exits. This can be very useful for testing. To use it, specify sqlite:///:memory: as the argument to create_engine(). The create_engine() function can also be used in a similar way with other RDBMSs. For example, to connect to the database my_database on a MySQL server at some.domain.com with the username foo and the password bar, you could use mysql://foo:[email protected]/my_database .

Different databases use different markers (known as param styles) to label where the variables you pass to execute() should be inserted. The example above used SQLite which uses ? as the param style but if you tried to use MySQL or PostgreSQL you would need to use %s as the param style instead. The SQL would then look like this: connection.execute( """ INSERT INTO users (username, password) VALUES (%s, %s); """, "foo", "bar" ) Using """ characters to mark the begining and end of the SQL allows you to use " and ' characters as part of the SQL and also allows you to add line breaks if your SQL statements get very long.

使用MetaData定义你的表结构

metadata_test.py

from sqlalchemy import schema, types

metadata = schema.MetaData()

#To represent a Table, use the Table class:
page_table = schema.Table('page', metadata,
        schema.Column('id', types.Integer, primary_key=True),
        schema.Column('name', types.Unicode(255), default=u''),
        schema.Column('title', types.Unicode(255), default=u'Untitled Page'),
        schema.Column('content', types.Text(), default=u''),
)

## MetaData object's methods:
# getting a list of Tables in the order (or reverse) of their dependency:
for t in metadata.sorted_tables:
    print "Table name: ", t.name

## Table' s methods
for c in page_table.columns:
    print "Column: ", c.name, c.type

for pk in page_table.primary_key:
    print "primay_key: ", pk

for fk in page_table.foreign_keys:
    print "foreign_keys: ", fk

Here you've created a metadata object from schema.MetaData, which will hold all the information about the tables, columns, types, foreign keys, indexes, and sequences that make up the database structure.
在虚拟环境中运行这个脚本，得到如下输入：

(env)forrest@ubuntu:~/Install/virtualenv-1.4.5/env/SimpleSite/simplesite/model$ python metadata_test.py 
Table name:  page
Column:  id Integer()
Column:  name Unicode(length=255)
Column:  title Unicode(length=255)
Column:  content Text(length=None, convert_unicode=False, assert_unicode=None)
primay_key:  page.id

sqlalchemy基本上支持所有的数据库类型定义，还允许用户自定义数据库类型，具体参见官方文档Column and Data Types

邦定MetaData到引擎

At this stage, the metadata is just information; it doesn't relate to any properties of a real database. To connect the metadata to a real database, you need to bind the metadata object to an engine.

metadata_bind_test.py

from sqlalchemy import schema, types
from sqlalchemy.engine import create_engine

metadata = schema.MetaData()

#To represent a Table, use the Table class:
page_table = schema.Table('page', metadata,
        schema.Column('id', types.Integer, primary_key=True),
        schema.Column('name', types.Unicode(255), default=u''),
        schema.Column('title', types.Unicode(255), default=u'Untitled Page'),
        schema.Column('content', types.Text(), default=u''),
)

## MetaData object's methods:
# getting a list of Tables in the order (or reverse) of their dependency:
for t in metadata.sorted_tables:
    print "Table name: ", t.name

## Table' s methods
for c in page_table.columns:
    print "Column: ", c.name, c.type

for pk in page_table.primary_key:
    print "primay_key: ", pk

for fk in page_table.foreign_keys:
    print "foreign_keys: ", fk

# 使用in-memory SQLite database
engine = create_engine('sqlite:///:memory:')
# 邦定metadata到数据库引擎，这样metadata就可以利用引擎真实操作数据库了（反过来，数据库引擎也可以利用metadata的信息作有意义的操作）
metadata.bind = engine

＃如果metadata中定义的表还没有存在数据库中，可以使用metadata.create_all方法来自动创建他们
＃checkfirst=True表示create the table only if it doesn't already exist.
metadata.create_all(checkfirst=True)

Tip It is worth being aware that you can have SQLAlchemy automatically convert all string types to handle Unicode automatically if you set up the engine like this: create_engine('sqlite:///:memory:', convert_unicode=True)

Reflecting Tables 反过来，如果数据库中定义的表还没有在metadata中声明，你也可以SQLAlchemy自动加载/反映(autoload=True, reflect)这些信息。需要注意的是此时的metadata必须已经邦定一个engine或者connection。 comment_table = schema.Table('comment', metadata, autoload=True) 具体参见官方文档Reflecting Tables

SQL Expression API

sqlexpression_test.py

from metadata_bind_test import engine, page_table

print "\nSQL Expression Example\n"

connection = engine.connect()

ins = page_table.insert(
        values=dict(name=u'test', title=u'Test Page',  content=u'Some content!')
)

print ins

result = connection.execute(ins)

print "\nSelecting Results\n"

from sqlalchemy.sql import select

s = select([page_table])
result = connection.execute(s)
for row in result:
    print row

print "\nUpdating Results\n"

from sqlalchemy import update

u = update(page_table, page_table.c.title==u'Test Page')
connection.execute(u, title=u"New Title")
print "\nAfter Update\n"
s = select([page_table])
result = connection.execute(s)
print result.fetchall()

print "\nDeleting Row\n"

from sqlalchemy import delete

d = delete(page_table, page_table.c.title==u'New Title')
connection.execute(d)

print "\nAfter Delete\n"
s = select([page_table])
result = connection.execute(s)
print result.fetchall()

connection.close()

运行，得到如下输出：

(env)forrest@ubuntu:~/Install/virtualenv-1.4.5/env/SimpleSite/simplesite/model$ python sqlexpression_test.py 
Table name:  page
Column:  id Integer()
Column:  name Unicode(length=255)
Column:  title Unicode(length=255)
Column:  content Text(length=None, convert_unicode=False, assert_unicode=None)
primay_key:  page.id
2011-01-06 21:01:41,556 INFO sqlalchemy.engine.base.Engine.0x...31d0 PRAGMA table_info("page")
2011-01-06 21:01:41,556 INFO sqlalchemy.engine.base.Engine.0x...31d0 ()
2011-01-06 21:01:41,556 INFO sqlalchemy.engine.base.Engine.0x...31d0 
CREATE TABLE page (
	id INTEGER NOT NULL, 
	name VARCHAR(255), 
	title VARCHAR(255), 
	content TEXT, 
	PRIMARY KEY (id)
)


2011-01-06 21:01:41,556 INFO sqlalchemy.engine.base.Engine.0x...31d0 ()
2011-01-06 21:01:41,557 INFO sqlalchemy.engine.base.Engine.0x...31d0 COMMIT

SQL Expression Example

INSERT INTO page (name, title, content) VALUES (?, ?, ?)
2011-01-06 21:01:41,557 INFO sqlalchemy.engine.base.Engine.0x...31d0 INSERT INTO page (name, title, content) VALUES (?, ?, ?)
2011-01-06 21:01:41,557 INFO sqlalchemy.engine.base.Engine.0x...31d0 [u'test', u'Test Page', u'Some content!']
2011-01-06 21:01:41,557 INFO sqlalchemy.engine.base.Engine.0x...31d0 COMMIT

Selecting Results

2011-01-06 21:01:41,558 INFO sqlalchemy.engine.base.Engine.0x...31d0 SELECT page.id, page.name, page.title, page.content 
FROM page
2011-01-06 21:01:41,558 INFO sqlalchemy.engine.base.Engine.0x...31d0 []
(1, u'test', u'Test Page', u'Some content!')

Updating Results

2011-01-06 21:01:41,558 INFO sqlalchemy.engine.base.Engine.0x...31d0 UPDATE page SET title=? WHERE page.title = ?
2011-01-06 21:01:41,558 INFO sqlalchemy.engine.base.Engine.0x...31d0 [u'New Title', u'Test Page']
2011-01-06 21:01:41,558 INFO sqlalchemy.engine.base.Engine.0x...31d0 COMMIT

After Update

2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 SELECT page.id, page.name, page.title, page.content 
FROM page
2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 []
[(1, u'test', u'New Title', u'Some content!')]

Deleting Row

2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 DELETE FROM page WHERE page.title = ?
2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 [u'New Title']
2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 COMMIT

After Delete

2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 SELECT page.id, page.name, page.title, page.content 
FROM page
2011-01-06 21:01:41,559 INFO sqlalchemy.engine.base.Engine.0x...31d0 []
[]

可以看到，ins对象自动生成正确的插入SQL语句。实际上connection.execute()方法可以接受SQL语句，所以我们也可以这么写：

connection = engine.connect()

sql = "INSERT INTO page (name, title, content ) VALUES ('%s', '%s', '%s')" % ("test", "Test Page", "Some Content")
result = connection.execute(sql)
connection.close()

在上面这个例子中，我们是手动打开关闭链接，实际上可以让metadata帮我们做这个事情：

ins = page_table.insert(
    values=dict(na
  

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