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76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from __future__ import annotations
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import csv
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from datetime import datetime
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from io import BytesIO, StringIO
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from typing import Any
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import pandas as pd
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import pytest
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from werkzeug.datastructures import FileStorage
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@pytest.fixture
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def dttm() -> datetime:
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return datetime.strptime("2019-01-02 03:04:05.678900", "%Y-%m-%d %H:%M:%S.%f")
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def create_csv_file(
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data: list[list[str]] | None = None, delimiter=",", filename="test.csv"
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) -> FileStorage:
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data = (
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[
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["Name", "Age", "City"],
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["John", "30", "New York"],
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]
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if not data
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else data
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)
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output = StringIO()
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writer = csv.writer(output, delimiter=delimiter)
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for row in data:
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writer.writerow(row)
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output.seek(0)
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buffer = BytesIO(output.getvalue().encode("utf-8"))
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return FileStorage(stream=buffer, filename=filename)
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def create_excel_file(
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data: dict[str, list[Any]] | None = None, filename="test.xls"
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) -> FileStorage:
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data = {"Name": ["John"], "Age": [30], "City": ["New York"]} if not data else data
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buffer = BytesIO()
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df = pd.DataFrame(data)
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df.to_excel(buffer, index=False)
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buffer.seek(0)
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return FileStorage(stream=buffer, filename=filename)
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def create_columnar_file(
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data: dict[str, list[Any]] | None = None, filename="test.parquet"
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) -> FileStorage:
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data = {"Name": ["John"], "Age": [30], "City": ["New York"]} if not data else data
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buffer = BytesIO()
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df = pd.DataFrame(data)
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df.to_parquet(buffer, index=False)
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buffer.seek(0)
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return FileStorage(stream=buffer, filename=filename)
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