| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| import logging |
| |
| import pandas as pd |
| |
| from hamilton.function_modifiers import tag |
| |
| logger = logging.getLogger(__name__) |
| |
| |
| @tag(cache="str") |
| def lowercased(initial: str) -> str: |
| logger.info("lowercased") |
| return initial.lower() |
| |
| |
| @tag(cache="str") |
| def uppercased(initial: str) -> str: |
| logger.info("uppercased") |
| return initial.upper() |
| |
| |
| @tag(cache="json") |
| def both(lowercased: str, uppercased: str) -> dict: |
| logger.info("both") |
| return {"lower": lowercased, "upper": uppercased} |
| |
| |
| def b2(both: dict) -> dict: |
| logger.info("b2") |
| return both |
| |
| |
| @tag(cache="json") |
| def my_df() -> pd.DataFrame: |
| logger.info("json df") |
| return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) |
| |
| |
| @tag(cache="json") |
| def my_series() -> pd.Series: |
| logger.info("json series") |
| return pd.Series([7, 8, 9]) |
| |
| |
| @tag(cache="parquet") |
| def my_df2(my_df: pd.DataFrame) -> pd.DataFrame: |
| logger.info("parquet df") |
| return my_df |
| |
| |
| @tag(cache="parquet") |
| def my_series2(my_series: pd.Series) -> pd.Series: |
| logger.info("parquet series") |
| return my_series |
| |
| |
| def combined(my_df2: pd.DataFrame, my_series2: pd.Series) -> pd.DataFrame: |
| logger.info("combined") |
| _s = pd.Series(my_series2, name="c") |
| _df = pd.concat([my_df2, _s], axis=1) |
| return _df |