当属性不遵守命名规则时python中的数据类

Question

If you have data like this (from a yaml file):

items:
  C>A/G>T: "#string"
  C>G/G>C: "#string"
  ...

How would load that in a dataclass that is explicit about the keys and type it has? Ideally I would have:

@dataclasses.dataclass
class X:
    C>A/G>T: str
    C>G/G>C: str
...

Update:

SBS_Mutations = TypedDict(
    "SBS_Mutations",
    {
        "C>A/G>T": str,
        "C>G/G>C": str,
        "C>T/G>A": str,
        "T>A/A>T": str,
        "T>C/A>G": str,
        "T>G/A>C": str,
    },
)

my_data = {....}

SBS_Mutations(my_data) # not sure how to use it here

Answer 1

if you want symbols like that, they obviously can't be Python identifiers, and then, it is meaningless to want to use the facilities that a dataclass, with attribute access, gives you.

Just keep your data in dictionaries, or in Pandas dataframes, where such names can be column titles.

Otherwise, post a proper code snippet with a minimum example of where you are getting the data from, and then, one can add in an answer, a proper place to translate your orignal name into a valid Python attribute name, and help building a dynamic data class with it.

Answer 2

This sounds like a good use case for my dotwiz library, which I have recently published. This provides a dict subclass which enables attribute-style dot access for nested keys.

As of the recent release, it offers a DotWizPlus implementation (a wrapper around a dict object) that also case transforms keys so that they are valid lower-cased, python identifier names, as shown below.

# requires the following dependencies:
#   pip install PyYAML dotwiz
import yaml
from dotwiz import DotWizPlus

yaml_str = """
items:
  C>A/G>T: "#string"
  C>G/G>C: "#string"
"""

yaml_dict = yaml.safe_load(yaml_str)
print(yaml_dict)

dw = DotWizPlus(yaml_dict)
print(dw)

assert dw.items.c_a_g_t == '#string'  # True

print(dw.to_attr_dict())

Output:

{'items': {'C>A/G>T': '#string', 'C>G/G>C': '#string'}}
✪(items=✪(c_a_g_t='#string', c_g_g_c='#string'))
{'items': {'c_a_g_t': '#string', 'c_g_g_c': '#string'}}

NB : This currently fails when accessing the key items from just a DotWiz instance, as the key name conflicts with the builtin attribute dict.items() . I've currently submitted a bug request and hopefully work through this one edge case in particular.

Type Hinting

If you want type-hinting or auto-suggestions for field names, you can try something like this where you subclass from DotWizPlus :

import yaml
from dotwiz import DotWizPlus


class Item(DotWizPlus):
    c_a_g_t: str
    c_g_g_c: str

    @classmethod
    def from_yaml(cls, yaml_string: str, loader=yaml.safe_load):
        yaml_dict = loader(yaml_str)
        return cls(yaml_dict['items'])


yaml_str = """
items:
  C>A/G>T: "#string1"
  C>G/G>C: "#string2"
"""

dw = Item.from_yaml(yaml_str)
print(dw)
# ✪(c_a_g_t='#string1', c_g_g_c='#string2')

assert dw.c_a_g_t == '#string1'  # True

# auto-completion will work, as IDE knows the type is a `str`
# dw.c_a_g_t.

Dataclasses

If you would still prefer dataclasses for type-hinting purposes, there is another library you can also check out called dataclass-wizard , which can help to simplify this task as well.

More specifically, YAMLWizard makes it easier to load/dump a class object with YAML. Note that this uses the PyYAML library behind the scenes by default.

Note that I couldn't get the case-transform to work in this case, since I guess it's a bug in the underlying to_snake_case() implementation. I'm also going to submit a bug request to look into this edge case. However, for now it should work if the key name in YAML is specified a bit more explicitly:

from dataclasses import dataclass

from dataclass_wizard import YAMLWizard, json_field

yaml_str = """
items:
  C>A/G>T: "#string"
  C>G/G>C: "#string"
"""


@dataclass
class Container(YAMLWizard):
    items: 'Item'


@dataclass
class Item:
    c_a_g_t: str = json_field('C>A/G>T')
    c_g_g_c: str = json_field('C>G/G>C')


c = Container.from_yaml(yaml_str)
print(c)

# True
assert c.items.c_g_g_c == c.items.c_a_g_t == '#string'

Output:

Container(items=Item(c_a_g_t='#string', c_g_g_c='#string'))