Python轻量级ORM Peewee 教程与特性概览

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Peewee 是一个轻量级的 Python Object-Relational Mapping (ORM) 库，旨在提供简单且强大的数据库操作能力。它具有以下几个关键特点： 1. **设计理念**：Peewee 专注于小而强大，拥有简洁的概念，使得学习曲线平缓，易于理解和使用。 2. **编程语言支持**：该库是用 Python 编写，支持 Python 2.6 及以上版本，以及 Python 3.2 及以上的兼容性。 3. **数据库支持**：内置了对 SQLite、MySQL 和 PostgreSQL 的支持，用户可以根据需求选择不同的数据库管理系统。 4. **扩展性**：Peewee 提供了丰富的扩展，如 Postgres HStore、JSON、数组支持，SQLite 的全文搜索功能，以及用于数据库结构迁移的工具，极大地增强了其功能范围。 5. **安装与测试**：文档提供了安装和测试指南，帮助用户快速上手并确保正确运行。 6. **示例应用**：1.3 节的 "Example app" 部分可能包含实际项目的代码示例，以展示 Peewee 如何在实际环境中工作。 7. **资源链接**：文档还列出了额外的学习资源，有助于新手更深入地了解和利用 Peewee。 8. **贡献指南**：对于希望参与开发或改进的用户，文档提供了关于如何贡献代码和修复问题的指导。 9. **数据库管理**：章节 1.6 提供了数据库的管理和维护方法，包括备份、恢复等实用技巧。 10. **模型与字段**：1.7 节详细介绍了如何创建和定义模型（数据模型）以及字段的定义和特性。 11. **查询操作**：Peewee 提供了强大的查询功能，包括基础查询、高级查询操作和复杂查询语句的编写。 12. **查询操作符**：1.9 部分涵盖了一系列查询操作符，允许用户灵活地构建查询条件。 13. **外键支持**：对于关联数据处理，1.11 节涉及外键关系的定义和使用。 14. **性能优化**：1.12 部分提供了提高 Peewee 性能的策略和技术，如缓存、查询优化等。 15. **事务处理**：为了确保数据一致性，文档解释了如何在 Peewee 中处理事务。 16. **Peewee 插件 Playhouse**：1.13 节介绍了 Playhouse 这一扩展，它为 Peewee 添加了额外的功能，如表设计和数据迁移工具。 17. **API参考**：详尽的 API 参考手册位于 1.14 节，为开发者提供了查阅 Peewee 功能和方法的完整指南。 18. **技巧与窍门**：1.15 部分可能会列出一些实用的黑客技巧和解决方案，帮助用户解决遇到的问题。通过阅读这些内容，初学者可以全面了解 Peewee ORM，并逐步掌握其核心功能和扩展能力，为自己的 Python 数据库项目打下坚实的基础。

peewee Documentation, Release 2.8.1

• Integers, ﬂoats, and Decimal numbers.

• Boolean values

• Dates, times and datetimes

• None (NULL)

• Binary data

Creating tables

In order to start using the models, its necessary to create the tables. This is a one-time operation and can be done

quickly using the interactive interpreter. We can create a small helper function to accomplish this:

def create_tables():

database.connect()

database.create_tables([User, Relationship, Message])

Open a python shell in the directory alongside the example app and execute the following:

>>> from app import

>>> create_tables()

Note: If you encounter an ImportError it means that either ﬂask or peewee was not found and may not be installed

correctly. Check the Installing and Testing document for instructions on installing peewee.

Every model has a create_table() classmethod which runs a SQL CREATE TABLE statement in the database.

This method will create the table, including all columns, foreign-key constraints, indexes, and sequences. Usually this

is something you’ll only do once, whenever a new model is added.

Peewee provides a helper method Database.create_tables() which will resolve inter-model dependencies

and call create_table() on each model.

Note: Adding ﬁelds after the table has been created will required you to either drop the table and re-create it or

manually add the columns using an ALTER TABLE query.

Alternatively, you can use the schema migrations extension to alter your database schema using Python.

Note: You can also write database.create_tables([User, ...], True) and peewee will ﬁrst check

to see if the table exists before creating it.

Establishing a database connection

You may have noticed in the above model code that there is a class deﬁned on the base model named Meta that sets

the database attribute. Peewee allows every model to specify which database it uses. There are many Meta options

you can specify which control the behavior of your model.

This is a peewee idiom:

DATABASE = 'tweepee.db'

# Create a database instance that will manage the connection and

12 Chapter 1. Contents:

peewee Documentation, Release 2.8.1

• Support for paginating lists of results is implemented in a simple function called object_list (after it’s

corollary in Django). This function is used by all the views that return lists of objects.

def object_list(template_name, qr, var_name='object_list',

kwargs):

kwargs.update(

page=int(request.args.get(

'page', 1)),

pages=qr.count() / 20 + 1

)

kwargs[var_name] = qr.paginate(kwargs['page'])

return render_template(template_name,

kwargs)

• Simple authentication system with a login_required decorator. The ﬁrst function simply adds user data

into the current session when a user successfully logs in. The decorator login_required can be used to

wrap view functions, checking for whether the session is authenticated and if not redirecting to the login page.

def auth_user(user):

session['logged_in'] = True

session['user'] = user

session['username'] = user.username

flash('You are logged in as %s' % (user.username))

def login_required(f):

@wraps(f)

def inner(

args,

kwargs):

if not session.get('logged_in'):

return redirect(url_for('login'))

return f(

args,

kwargs)

return inner

• Return a 404 response instead of throwing exceptions when an object is not found in the database.

def get_object_or_404(model,

expressions):

try:

return model.get(

expressions)

except model.DoesNotExist:

abort(404)

1.3.3 More examples

There are more examples included in the peewee examples directory, including:

• Example blog app using Flask and peewee. Also see accompanying blog post.

• An encrypted command-line diary. There is a companion blog post you might enjoy as well.

• Analytics web-service (like a lite version of Google Analytics). Also check out the companion blog post.

Note: Like these snippets and interested in more? Check out ﬂask-peewee - a ﬂask plugin that provides a django-like

Admin interface, RESTful API, Authentication and more for your peewee models.

1.4 Additional Resources

I’ve written a number of blog posts about building applications and web-services with peewee (and usually Flask). If

you’d like to see some “real-life” applications that use peewee, the following resources may be useful:

1.4. Additional Resources 15

peewee Documentation, Release 2.8.1

• How to make a Flask blog in one hour or less.

• Building a note-taking app with Flask and Peewee as well as Part 2 and Part 3.

• Analytics web service built with Flask and Peewee.

• Personalized news digest (with a boolean query parser!).

• Using peewee to explore CSV ﬁles.

• Structuring Flask apps with Peewee.

• Creating a lastpass clone with Flask and Peewee.

• Building a web-based encrypted ﬁle manager with Flask, peewee and S3.

• Creating a bookmarking web-service that takes screenshots of your bookmarks.

• Building a pastebin, wiki and a bookmarking service using Flask and Peewee.

• Encrypted databases with Python and SQLCipher.

• Dear Diary, an Encrypted Command-Line Diary.

1.5 Contributing

In order to continually improve, Peewee needs the help of developers like you. Whether it’s contributing patches,

submitting bug reports, or just asking and answering questions, you are helping to make Peewee a better library.

In this document I’ll describe some of the ways you can help.

1.5.1 Patches

Do you have an idea for a new feature, or is there a clunky API you’d like to improve? Before coding it up and

submitting a pull-request, open a new issue on GitHub describing your proposed changes. This doesn’t have to be

anything formal, just a description of what you’d like to do and why.

When you’re ready, you can submit a pull-request with your changes. Successful patches will have the following:

• Unit tests.

• Documentation, both prose form and general API documentation.

• Code that conforms stylistically with the rest of the Peewee codebase.

1.5.2 Bugs

If you’ve found a bug, please check to see if it has already been reported, and if not create an issue on GitHub. The

more information you include, the more quickly the bug will get ﬁxed, so please try to include the following:

• Traceback and the error message (please format your code!)

• Relevant portions of your code or code to reproduce the error

• Peewee version: python -c "from peewee import __version__; print(__version__)"

• Which database you’re using

If you have found a bug in the code and submit a failing test-case, then hats-off to you, you are a hero!

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