| # 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 duckdb |
| import ibis |
| import ibis.expr.types as ir |
| import pandas as pd |
| import pyarrow |
| |
| from hamilton.function_modifiers import config |
| |
| |
| def pyarrow_table() -> pyarrow.Table: |
| """Create a duckdb table in-memory and return it as a PyArrow table""" |
| con = duckdb.connect(database=":memory:") |
| con.execute("CREATE TABLE items (item VARCHAR, value DECIMAL(10, 2), count INTEGER)") |
| con.execute("INSERT INTO items VALUES ('jeans', 20.0, 1), ('hammer', 42.2, 2)") |
| return con.execute("SELECT * FROM items").fetch_arrow_table() |
| |
| |
| def ibis_rename(pyarrow_table: pyarrow.Table) -> ir.Table: |
| """Rename the columns""" |
| table = ibis.memtable(pyarrow_table) |
| return table.rename(object="item", price="value", number="count") |
| |
| |
| @config.when(version="1") |
| def pandas_new_col__v1(ibis_rename: ir.Table) -> pd.DataFrame: |
| """Add the column `new_col`""" |
| df = ibis_rename.to_pandas() |
| df["col_a"] = True |
| return df |
| |
| |
| @config.when(version="2") |
| def pandas_new_col__v2(ibis_rename: ir.Table) -> pd.DataFrame: |
| """Add the columns `new_col` and `another_col`""" |
| df = ibis_rename.to_pandas() |
| df["col_a"] = True |
| df["col_b"] = "X" |
| return df |
| |
| |
| @config.when(version="3") |
| def pandas_new_col__v4(ibis_rename: ir.Table) -> pd.DataFrame: |
| """Add the column `new_col` of type float""" |
| df = ibis_rename.to_pandas() |
| df["col_a"] = 1.0 |
| return df |
| |
| |
| if __name__ == "__main__": |
| import argparse |
| import json |
| |
| import __main__ |
| from hamilton import driver |
| from hamilton.plugins import h_schema |
| |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--version", default="1", type=str, help="The Driver config version") |
| parser.add_argument( |
| "--no-check", action="store_false", help="Disable `check` to update the stored schemas." |
| ) |
| args = parser.parse_args() |
| validator_adapter = h_schema.SchemaValidator( |
| "./multi_schemas", check=args.no_check, importance="warn" |
| ) |
| dr = ( |
| driver.Builder() |
| .with_modules(__main__) |
| .with_config(dict(version=args.version)) |
| .with_adapters(validator_adapter) |
| .build() |
| ) |
| res = dr.execute(["pandas_new_col"]) |
| print(res["pandas_new_col"].head()) |
| print() |
| |
| print(json.dumps(validator_adapter.json_schemas, indent=2)) |