从pydantic对象列表中创建JSON字符串列表
我正在尝试从pydantic对象列表中获取JSON字符串列表，并以下面的方式完成：
raw_books = [json.dumps(x.dict()) for x in batch.books]
一切正常，但是当列表包含数千个元素时，似乎需要很多时间。更有效地进行这种转变的另一种方法是什么？
例如： batch.books中的2000个列表元素导致执行时间约为5秒。
Pydantic模型：
class Book(BaseModel):
title: constr(min_length=1, max_length=128)
authors: List[constr(min_length=1, max_length=128)]
price: float
year_of_publishing: int
publisher: constr(min_length=1, max_length=128)
class BulkBook(BaseModel):
books: List[Book]
I am trying to get a list of json strings from a list of Pydantic objects and have done it in the following way:
raw_books = [json.dumps(x.dict()) for x in batch.books]
Everything works fine, but it seems to take a lot of time when the list holds thousands of elements. What would be another way to do this transformation more efficiently?
For example: 2000 list elements in batch.books result in execution times of around 5 seconds.
The pydantic model(s):
class Book(BaseModel):
title: constr(min_length=1, max_length=128)
authors: List[constr(min_length=1, max_length=128)]
price: float
year_of_publishing: int
publisher: constr(min_length=1, max_length=128)
class BulkBook(BaseModel):
books: List[Book]
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评论（2）
因此我们谈论的是
5000/2000 每个list的MS，对吗？2.5用于转换list的MS（您在哪些元素上json.dumps（x.dict（））））不是这样我猜很长一段时间。So we are talking of about
5000/2000ms for eachlist, right?2.5ms for the conversion of alist(on which elements you are callingjson.dumps(x.dict())) it's not such a long time I guess.您正在调用
json.dumps<代码>列表理解，这似乎是一个问题。预计这确实会导致性能大幅下降，因为dumps在循环中的每次迭代都调用。最简单的解决方案是将
json.dumps移出list完全理解：You are calling
json.dumpsinside thelistcomprehension, that seems to be a problem. That would be expected do cause a huge dip in performance, becausedumpsis called for each iteration in the loop.The simplest solution would be to move
json.dumpsout of thelistcomprehension entirely: