blob: 3a6fb0e0a5f50f1afe33f9986c8d1a51c3fd2088 [file] [log] [blame]
import logging
import pandas as pd
from hamilton.function_modifiers import tag
@tag(cache="str")
def lowercased(initial: str) -> str:
logging.info("lowercased")
return initial.lower()
@tag(cache="str")
def uppercased(initial: str) -> str:
logging.info("uppercased")
return initial.upper()
@tag(cache="json")
def both(lowercased: str, uppercased: str) -> dict:
logging.info("both")
return {"lower": lowercased, "upper": uppercased}
def b2(both: dict) -> dict:
logging.info("b2")
return both
@tag(cache="json")
def my_df() -> pd.DataFrame:
logging.info("json df")
return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
@tag(cache="json")
def my_series() -> pd.Series:
logging.info("json series")
return pd.Series([7, 8, 9])
@tag(cache="parquet")
def my_df2(my_df: pd.DataFrame) -> pd.DataFrame:
logging.info("parquet df")
return my_df
@tag(cache="parquet")
def my_series2(my_series: pd.Series) -> pd.Series:
logging.info("parquet series")
return my_series
def combined(my_df2: pd.DataFrame, my_series2: pd.Series) -> pd.DataFrame:
logging.info("combined")
_s = pd.Series(my_series2, name="c")
_df = pd.concat([my_df2, _s], axis=1)
return _df