SQLAlchemy 并通过一个大的结果集 [英] SQLAlchemy and going through a large result set

问题描述

我需要从一个大表的所有行中读取数据，但我不想一次将所有数据拉入内存.是否有处理分页的 SQLAlchemy 函数?也就是说，将几行拉入内存，然后在必要时获取更多行.

I need to read data from all of the rows of a large table, but I don't want to pull all of the data into memory at one time. Is there a SQLAlchemy function that will handle paging? That is, pull several rows into memory and then fetch more when necessary.

我知道您可以使用 limit 和 offset 作为 这篇文章 建议，但如果我没有必要，我宁愿不处理.

I understand you can do this with limit and offset as this article suggests, but I'd rather not handle that if I don't have to.

推荐答案

如果您使用的是 Flask-SqlAlchemy，请参阅 分页 方法.paginate 提供了几种简化分页的方法.

If you are using Flask-SqlAlchemy, see the paginate method of query. paginate offers several method to simplify pagination.

record_query = Record.query.paginate(page, per_page, False)
total = record_query.total
record_items = record_query.items

第一页应该是 1 否则 .total 返回除以零的异常

First page should be 1 otherwise the .total returns exception divided by zero

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