python数据库/ sql编程 - 从哪里开始 [英] python database / sql programming - where to start

问题描述

使用嵌入式数据库的最佳方法是在Python中使用sqlite：

What is the best way to use an embedded database, say sqlite in Python:

1. 我每表只需要几千条记录。


2. 如果它是由Python默认安装提供的，那么很好。必须是开源的，在Windows和Linus上可用。


3. 如果SQL不是直接写入，更好，但不完全需要ORM。某事，将屏蔽我从实际的数据库，但不是那么大的图书馆。


4. 大部分将通过代码使用，但如果有一个GUI前端，那么这是很好的


5. 只需要几页的开始。我不想通过阅读一个表是什么，以及Select语句如何工作。我知道所有这一切。


6. 支持Python 3是首选，但是2.x也可以。

1. Should be small footprint. I'm only needing few thousands records per table. And just a handful of tables per database.
2. If it's one provided by Python default installation, then great. Must be open-source, available on Windows and Linus.
3. Better if SQL is not written directly, but no ORM is fully needed. Something that will shield me from the actual database, but not that huge of a library. Something similar to ADO will be great.
4. Mostly will be used through code, but if there is a GUI front end, then that is great
5. Need just a few pages to get started with. I don't want to go through pages reading what a table is and how a Select statement works. I know all of that.
6. Support for Python 3 is preferred, but 2.x is okay too.

使用不是网络应用程序。它是一个小数据库，最多可容纳5个表。每个表中的数据只是几个字符串列。

更新：非常感谢您的建议。

我在说的用例是相当简单。

这是一个100行的Python脚本，它收集有关大量文件（例如10k）的数据，并创建有关它们的元数据文件，然后一个关于整个文件树的大元数据文件。我只需要避免重新处理已处理的文件，并为更新的文件创建元数据，并更新主元数据文件。在某种程度上，缓存处理的数据，并且只在文件更新时更新它。
如果缓存已损坏/不可用，那么只需处理整个树。这可能需要20分钟，但是没关系。

Update: Many thanks for the great suggestions.
The use-case I'm talking about is fairly simple. One you'd probably do in a day or two.
It's a 100ish line Python script that gathers data about a relatively large number of files (say 10k), and creates metadata files about them, and then one large metadata file about the whole files tree. I just need to avoid re-processing the files already processed, and create the metadata for the updated files, and update the main metadata file. In a way, cache the processed data, and only update it on file updates. If the cache is corrupt / unavailable, then simply process the whole tree. It might take 20 minutes, but that's okay.

请注意，所有处理都是在内存中完成。

Note that all processing is done in-memory.

我想避免任何外部依赖，以便脚本可以轻松地放在任何系统上只有一个Python安装上。作为Windows，有时很难安装所有组件。
所以，在我看来，即使是一个数据库可能是一个过度。

I would like to avoid any external dependencies, so that the script can easily be put on any system with just a Python installation on it. Being Windows, it is sometimes hard to get all the components installed. So, In my opinion, even a database might be an overkill.

您可能不会启动一个Office Word / Writer写一个小的帖子类型笔记，类似地，我不愿意使用像Django这样的用例。

You probably wouldn't fire up an Office Word/Writer to write a small post it type note, similarly I am reluctant on using something like Django for this use-case.

从哪里开始？

推荐答案

答案，没有特定的顺序：

This is an aggregate of answers, in no particular order:

每个人都在推荐一个ORM层。这使得完美的意义，如果你真的需要一个数据库。好吧，这是标题中请求的： - ）

Everybody is recommending an ORM layer. Which makes perfect sense, if you really need a database. Well, that was sort of requested in the title :-)

1. SQLAlchemy


2. 秋季< a>


3. Django ORM


4. 使用SQLite官方支持 Pysqlite


5. Storm


6. Elixir


7. 只需使用Python自己的Pickle

1. SQLAlchemy
2. Autumn
3. Django ORM
4. Use SQLite official support Pysqlite
5. Storm
6. Elixir
7. Just use Python's own Pickle

但我开始认为，如果一个内存数据库是足够的，在这将只在脚本，而不是一个web应用程序，甚至桌面gui，那么选项7也是完全有效的，只要没有事务需要支持，数据库完整性不是问题。

But I'm starting to think that if an in-memory database is sufficient, in this will be used in scripts only, not a web app or even a desktop gui, then option 7 is also perfectly valid, provided no transaction support is needed and "database" integrity is not an issue.

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