大多数自定义 python 对象的新 PyYAML 版本中断 - RepresenterError

New PyYAML version breaks on most custom python objects - RepresenterError(大多数自定义 python 对象的新 PyYAML 版本中断 - RepresenterError)

问题描述

大约 5 小时前，4.1.0 版本发布.它打破了我的单元测试.这是一个干净的 MVCE 显示:

About 5 hours ago, version 4.1.0 was released. It is breaking my unit tests. Here is a clean MVCE displaying this:

3.12 版:

>>> import numpy as np
>>> import yaml
>>> x = np.int64(2)
>>> yaml.dump(x, Dumper=yaml.Dumper)
'!!python/object/apply:numpy.core.multiarray.scalar
- !!python/object/apply:numpy.dtype
  args: [i8, 0, 1]
  state: !!python/tuple [3, <, null, null, null, -1, -1, 0]
- !!binary |
  AgAAAAAAAAA=
'

4.1.0 版:

>>> import numpy as np
>>> import yaml
>>> x = np.int64(2)
>>> yaml.dump(x, Dumper=yaml.Dumper)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/foo/anaconda3/envs/bar/lib/python3.6/site-packages/yaml/__init__.py", line 217, in dump
    return dump_all([data], stream, Dumper=Dumper, **kwds)
  File "/foo/anaconda3/envs/bar/lib/python3.6/site-packages/yaml/__init__.py", line 196, in dump_all
    dumper.represent(data)
  File "/foo/anaconda3/envs/bar/lib/python3.6/site-packages/yaml/representer.py", line 26, in represent
    node = self.represent_data(data)
  File "/foo/anaconda3/envs/bar/lib/python3.6/site-packages/yaml/representer.py", line 57, in represent_data
    node = self.yaml_representers[None](self, data)
  File "/foo/anaconda3/envs/bar/lib/python3.6/site-packages/yaml/representer.py", line 229, in represent_undefined
    raise RepresenterError("cannot represent an object", data)
yaml.representer.RepresenterError: ('cannot represent an object', 2)

PyYAML 不再支持这些对象类型有明确的原因吗?

Is there a clear reason for why PyYAML no longer supports these object types?

推荐答案

在 PyYAML 4.x 中，dump 是 safe_dump 的别名，不会处理任意对象:

In PyYAML 4.x, dump is an alias for safe_dump, which won't handle arbitrary objects:

>>> yaml.dump is yaml.safe_dump
True

对旧的 3.x 行为使用 danger_dump.

Use danger_dump for the old 3.x behaviour.

>>> yaml.danger_dump(x)
'!!python/object/apply:numpy.core.multiarray.scalar
- !!python/object/apply:numpy.dtype
  args: [i8, 0, 1]
  state: !!python/tuple [3, <, null, null, null, -1, -1, 0]
- !!binary |
  AgAAAAAAAAA=
'

load/safe_load 也是如此.找不到 4.1.0 的任何文档或发行说明，我只是通过挖掘提交才发现的 (这里).

The same goes for load/safe_load. Can't find any docs or release notes for 4.1.0, I only found out by digging through the commits (here).

PyYAML 不再支持这些对象类型有明确的原因吗?

Is there a clear reason for why PyYAML no longer supports these object types?

是的.yaml.load 允许任意代码执行，而这种危险的功能只能选择加入，不能意外使用.可以说，从一开始就应该是这样的.

Yes. yaml.load was allowing arbitrary code execution, and such a dangerous feature should be opt-in only, not possible to use by accident. Arguably, it should have been this way from the beginning.

在当前的 PyYAML 5.x 中:您可以指定 loader/dumper 类作为参数，而不是使用不同的函数:

In current PyYAML 5.x: instead of using different functions, you can specify the loader/dumper class as an argument:

yaml.dump(x, Dumper=yaml.Dumper)      # like "danger dump"
yaml.dump(x, Dumper=yaml.SafeDumper)  # like "safe_dump", won't dump python objs

与 3.x 一样，危险"dump 仍然是 5.x 中的默认值:

As with 3.x, the "danger" dump is still the default in 5.x:

>>> yaml.dump(sys)
"!!python/module:sys ''
"
>>> yaml.dump(sys, Dumper=yaml.SafeDumper)
RepresenterError: ('cannot represent an object', <module 'sys' (built-in)>)

这篇关于大多数自定义 python 对象的新 PyYAML 版本中断 - RepresenterError的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持编程学习网！