64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
'''
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Various pandas helpers and convenience functions
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'''
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# todo not sure if belongs to 'core'. It's certainly 'more' core than actual modules, but still not essential
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# NOTE: this file is meant to be importable without Pandas installed
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from datetime import datetime
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from typing import Optional, TYPE_CHECKING, Any
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from . import warnings
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if TYPE_CHECKING:
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# this is kinda pointless at the moment, but handy to annotate DF returning methods now
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# later will be unignored when they implement type annotations
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import pandas as pd # type: ignore
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# DataFrameT = pd.DataFrame
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DataFrameT = Any
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else:
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# in runtime, make it defensive so it works without pandas
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DataFrameT = Any
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def check_dateish(s) -> Optional[str]:
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import pandas as pd # type: ignore
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ctype = s.dtype
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if str(ctype).startswith('datetime64'):
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return None
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s = s.dropna()
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if len(s) == 0:
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return None
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all_timestamps = s.apply(lambda x: isinstance(x, (pd.Timestamp, datetime))).all()
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if all_timestamps:
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return 'All values are timestamp-like, but dtype is not datetime. Most likely, you have mixed timezones'
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return None
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from typing import Any, Callable, TypeVar
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FuncT = TypeVar('FuncT', bound=Callable[..., DataFrameT])
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def check_dataframe(f: FuncT) -> FuncT:
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from functools import wraps
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@wraps(f)
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def wrapper(*args, **kwargs) -> DataFrameT:
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df = f(*args, **kwargs)
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# todo make super defensive?
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for col, data in df.reset_index().iteritems():
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res = check_dateish(data)
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if res is not None:
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warnings.low(f"{f.__module__}:{f.__name__}, column '{col}': {res}")
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return df
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# https://github.com/python/mypy/issues/1927
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return wrapper # type: ignore[return-value]
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# todo doctor: could have a suggesion to wrap dataframes with it?? discover by return type?
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from typing import Dict, Any
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from .error import extract_error_datetime
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def error_to_row(e: Exception, *, dt_col: str='dt') -> Dict[str, Any]:
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# TODO attach traceback?
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edt = extract_error_datetime(e)
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return {
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'error': str(e),
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dt_col : edt,
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}
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