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102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
import numpy as np
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import pytest
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from pandas import DataFrame, date_range, read_csv, read_parquet
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import pandas._testing as tm
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from pandas.util import _test_decorators as td
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df1 = DataFrame(
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{
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"int": [1, 3],
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"float": [2.0, np.nan],
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"str": ["t", "s"],
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"dt": date_range("2018-06-18", periods=2),
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}
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)
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# the ignore on the following line accounts for to_csv returning Optional(str)
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# in general, but always str in the case we give no filename
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text = df1.to_csv(index=False).encode() # type: ignore
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@pytest.fixture
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def cleared_fs():
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fsspec = pytest.importorskip("fsspec")
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memfs = fsspec.filesystem("memory")
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yield memfs
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memfs.store.clear()
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def test_read_csv(cleared_fs):
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from fsspec.implementations.memory import MemoryFile
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cleared_fs.store["test/test.csv"] = MemoryFile(data=text)
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df2 = read_csv("memory://test/test.csv", parse_dates=["dt"])
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tm.assert_frame_equal(df1, df2)
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def test_reasonable_error(monkeypatch, cleared_fs):
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from fsspec import registry
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from fsspec.registry import known_implementations
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registry.target.clear()
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with pytest.raises(ValueError) as e:
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read_csv("nosuchprotocol://test/test.csv")
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assert "nosuchprotocol" in str(e.value)
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err_mgs = "test error messgae"
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monkeypatch.setitem(
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known_implementations,
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"couldexist",
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{"class": "unimportable.CouldExist", "err": err_mgs},
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)
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with pytest.raises(ImportError) as e:
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read_csv("couldexist://test/test.csv")
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assert err_mgs in str(e.value)
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def test_to_csv(cleared_fs):
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df1.to_csv("memory://test/test.csv", index=True)
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df2 = read_csv("memory://test/test.csv", parse_dates=["dt"], index_col=0)
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tm.assert_frame_equal(df1, df2)
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@td.skip_if_no("fastparquet")
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def test_to_parquet_new_file(monkeypatch, cleared_fs):
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"""Regression test for writing to a not-yet-existent GCS Parquet file."""
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df1.to_parquet(
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"memory://test/test.csv", index=True, engine="fastparquet", compression=None
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)
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@td.skip_if_no("s3fs")
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def test_from_s3_csv(s3_resource, tips_file):
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tm.assert_equal(read_csv("s3://pandas-test/tips.csv"), read_csv(tips_file))
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# the following are decompressed by pandas, not fsspec
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tm.assert_equal(read_csv("s3://pandas-test/tips.csv.gz"), read_csv(tips_file))
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tm.assert_equal(read_csv("s3://pandas-test/tips.csv.bz2"), read_csv(tips_file))
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@pytest.mark.parametrize("protocol", ["s3", "s3a", "s3n"])
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@td.skip_if_no("s3fs")
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def test_s3_protocols(s3_resource, tips_file, protocol):
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tm.assert_equal(
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read_csv("%s://pandas-test/tips.csv" % protocol), read_csv(tips_file)
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)
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@td.skip_if_no("s3fs")
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@td.skip_if_no("fastparquet")
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def test_s3_parquet(s3_resource):
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fn = "s3://pandas-test/test.parquet"
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df1.to_parquet(fn, index=False, engine="fastparquet", compression=None)
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df2 = read_parquet(fn, engine="fastparquet")
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tm.assert_equal(df1, df2)
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@td.skip_if_installed("fsspec")
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def test_not_present_exception():
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with pytest.raises(ImportError) as e:
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read_csv("memory://test/test.csv")
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assert "fsspec library is required" in str(e.value)
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