Python Pydantic root_validator 可以对整个模型使用一次，而不是单个验证器吗

我正在使用PYDANIC创建一个基于PANDA TIMESTAMP(start,end)和Timedelta(period)对象的时间序列模型.该模型将用于一个具有多个配置/场景的小型数据分析程序.

我需要基于两个bool(include_end_period,allow_future)和一个可选int(max_periods)配置参数实例化和验证TimeSeries模型的各个方面.然后，我需要派生三个新字段(timezone、total_duration、total_periods)并执行一些额外的验证.

由于在验证另一个值时需要使用一个值的几个实例，我无法使用典型的@validator个方法获得所需的结果.特别是，我经常会得到一个丢失的KeyError，而不是预期的ValueError.我找到的最好的解决方案是创建一个长@root_validator(pre=True)方法.

from pydantic import BaseModel, ValidationError, root_validator, conint
from pandas import Timestamp, Timedelta


class Timeseries(BaseModel):
    start: Timestamp
    end: Timestamp
    period: Timedelta
    include_end_period: bool = False
    allow_future: bool = True
    max_periods: conint(gt=0, strict=True) | None = None
    
    # Derived values, do not pass as params
    timezone: str | None
    total_duration: Timedelta
    total_periods: conint(gt=0, strict=True)
    
    class Config:
        extra = 'forbid'
        validate_assignment = True
    
    
    @root_validator(pre=True)
    def _validate_model(cls, values):
        
        # Validate input values
        if values['start'] > values['end']:
            raise ValueError('Start timestamp cannot be later than end')
        if values['start'].tzinfo != values['end'].tzinfo:
            raise ValueError('Start, end timezones do not match')
        if values['period'] <= Timedelta(0):
            raise ValueError('Period must be a positive amount of time')
        
        # Set timezone
        timezone = values['start'].tzname()
        if 'timezone' in values and values['timezone'] != timezone:
            raise ValueError('Timezone param does not match start timezone')
        values['timezone'] = timezone
        
        # Set duration (add 1 period if including end period)
        total_duration = values['end'] - values['start']
        if values['include_end_period']:
            total_duration += values['period']
        if 'total_duration' in values and values['total_duration'] != total_duration:
            error_context = ' + 1 period (included end period)' if values['include_end_period'] else ''
            raise ValueError(f'Duration param does not match end - start timestamps{error_context}')
        values['total_duration'] = total_duration
        
        # Set total_periods
        periods_float: float = values['total_duration'] / values['period']
        if periods_float != int(periods_float):
            raise ValueError('Total duration not divisible by period length')
        total_periods = int(periods_float)
        if 'total_periods' in values and values['total_periods'] != total_periods:
            raise ValueError('Total periods param does not match')
        values['total_periods'] = total_periods
        
        # Validate future
        if not values['allow_future']:
            # Get current timestamp to floor of period (subtract 1 period if including end period)
            max_end: Timestamp = Timestamp.now(tz=values['timezone']).floor(freq=values['period'])
            if values['include_end_period']:
                max_end -= values['period']
            if values['end'] > max_end:
                raise ValueError('End period is future or current (incomplete)')
        
        # Validate derived values
        if values['total_duration'] < Timedelta(0):
            raise ValueError('Total duration must be positive amount of time')
        if values['max_periods'] and values['total_periods'] > values['max_periods']:
            raise ValueError('Total periods exceeds max periods param')
        
        return values

在令人满意的情况下实例化模型，使用所有配置判断:

start = Timestamp('2023-03-01T00:00:00Z')
end = Timestamp('2023-03-02T00:00:00Z')
period = Timedelta('5min')

try:
    ts = Timeseries(start=start, end=end, period=period,
                    include_end_period=True, allow_future=False, max_periods=10000)
    print(ts.dict())
except ValidationError as e:
    print(e)

输出:

"""
{'start': Timestamp('2023-03-01 00:00:00+0000', tz='UTC'),
 'end': Timestamp('2023-03-02 00:00:00+0000', tz='UTC'),
 'period': Timedelta('0 days 00:05:00'),
 'include_end_period': True,
 'allow_future': False,
 'max_periods': 10000,
 'timezone': 'UTC',
 'total_duration': Timedelta('1 days 00:05:00'),
 'total_periods': 289}
"""

在这里，我相信我的所有验证都像预期的那样工作，并提供了预期的ValueErrors，而不是帮助较小的KeyErrors.Is this approach reasonable?这似乎与典型的/推荐的方法背道而驰，与@validator相比，@root_validator的文档相当简短.

我还不满意需要在模型顶部列出派生值(timezone、total_duration、total_periods).这意味着它们可以/应该在实例化时传递，并且在我的验证器脚本中需要额外的逻辑来判断它们是否被传递，以及它们是否与派生的值匹配.如果省略它们，它们将不会从类型、约束等的默认验证中受益，并且会迫使我将配置更改为extra='allow'.如果有任何关于如何改进这方面的建议，我将不胜感激.

谢谢!