|
| 1 | +import logging |
| 2 | + |
| 3 | +import botocore |
| 4 | +import pandas as pd |
| 5 | +import pytest |
| 6 | + |
| 7 | +import awswrangler as wr |
| 8 | + |
| 9 | +logging.getLogger("awswrangler").setLevel(logging.DEBUG) |
| 10 | + |
| 11 | + |
| 12 | +@pytest.mark.parametrize("use_threads", [True, False]) |
| 13 | +def test_wait_object_exists_single_file(path: str, use_threads: bool) -> None: |
| 14 | + df = pd.DataFrame({"FooBoo": [1, 2, 3]}) |
| 15 | + file_path = f"{path}data.csv" |
| 16 | + |
| 17 | + wr.s3.to_csv(df, file_path) |
| 18 | + |
| 19 | + wr.s3.wait_objects_exist(paths=[file_path], use_threads=use_threads) |
| 20 | + |
| 21 | + |
| 22 | +@pytest.mark.parametrize("use_threads", [True, False]) |
| 23 | +def test_wait_object_exists_multiple_files(path: str, use_threads: bool) -> None: |
| 24 | + df = pd.DataFrame({"FooBoo": [1, 2, 3]}) |
| 25 | + |
| 26 | + file_paths = [f"{path}data.csv", f"{path}data2.csv", f"{path}data3.csv"] |
| 27 | + for file_path in file_paths: |
| 28 | + wr.s3.to_csv(df, file_path) |
| 29 | + |
| 30 | + wr.s3.wait_objects_exist(paths=file_paths, use_threads=use_threads) |
| 31 | + |
| 32 | + |
| 33 | +@pytest.mark.parametrize("use_threads", [True, False]) |
| 34 | +def test_wait_object_not_exists(path: str, use_threads: bool) -> None: |
| 35 | + wr.s3.wait_objects_not_exist(paths=[path], use_threads=use_threads) |
| 36 | + |
| 37 | + |
| 38 | +@pytest.mark.parametrize("use_threads", [True, False]) |
| 39 | +@pytest.mark.timeout(5) |
| 40 | +def test_wait_object_timeout(path: str, use_threads: bool) -> None: |
| 41 | + with pytest.raises(botocore.exceptions.WaiterError): |
| 42 | + wr.s3.wait_objects_exist( |
| 43 | + paths=[path], |
| 44 | + use_threads=use_threads, |
| 45 | + delay=0.5, |
| 46 | + max_attempts=3, |
| 47 | + ) |
| 48 | + |
| 49 | + |
| 50 | +@pytest.mark.parametrize("use_threads", [True, False]) |
| 51 | +def test_wait_object_exists_empty_list(use_threads: bool) -> None: |
| 52 | + wr.s3.wait_objects_exist(paths=[]) |
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