FM / io

/usr/local/lib64/python3.6/site-packages/pandas/tests/io/

/usr/local/lib64/python3.6/site-packages/pandas/tests/io

Name	Size	Mode	Actions
excel/	-	0755	rm
formats/	-	0755	rm
json/	-	0755	rm
parser/	-	0755	rm
pytables/	-	0755	rm
sas/	-	0755	rm
__pycache__/	-	0755	rm
conftest.py	2526	0644	edit dl rm
generate_legacy_storage_files.py	10074	0644	edit dl rm
test_clipboard.py	8028	0644	edit dl rm
test_common.py	13454	0644	edit dl rm
test_compression.py	6332	0644	edit dl rm
test_date_converters.py	1200	0644	edit dl rm
test_feather.py	6206	0644	edit dl rm
test_fsspec.py	3165	0644	edit dl rm
test_gbq.py	6810	0644	edit dl rm
test_gcs.py	2985	0644	edit dl rm
test_html.py	39222	0644	edit dl rm
test_orc.py	6482	0644	edit dl rm
test_parquet.py	28221	0644	edit dl rm
test_pickle.py	14440	0644	edit dl rm
test_s3.py	1535	0644	edit dl rm
test_spss.py	2745	0644	edit dl rm
test_sql.py	100660	0644	edit dl rm
test_stata.py	78257	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/io/test_fsspec.py (3165B)

import numpy as np
import pytest

from pandas import DataFrame, date_range, read_csv, read_parquet
import pandas._testing as tm
from pandas.util import _test_decorators as td

df1 = DataFrame(
    {
        "int": [1, 3],
        "float": [2.0, np.nan],
        "str": ["t", "s"],
        "dt": date_range("2018-06-18", periods=2),
    }
)
# the ignore on the following line accounts for to_csv returning Optional(str)
# in general, but always str in the case we give no filename
text = df1.to_csv(index=False).encode()  # type: ignore

@pytest.fixture
def cleared_fs():
    fsspec = pytest.importorskip("fsspec")

memfs = fsspec.filesystem("memory")
    yield memfs
    memfs.store.clear()

def test_read_csv(cleared_fs):
    from fsspec.implementations.memory import MemoryFile

cleared_fs.store["test/test.csv"] = MemoryFile(data=text)
    df2 = read_csv("memory://test/test.csv", parse_dates=["dt"])

tm.assert_frame_equal(df1, df2)

def test_reasonable_error(monkeypatch, cleared_fs):
    from fsspec import registry
    from fsspec.registry import known_implementations

registry.target.clear()
    with pytest.raises(ValueError) as e:
        read_csv("nosuchprotocol://test/test.csv")
        assert "nosuchprotocol" in str(e.value)
    err_mgs = "test error messgae"
    monkeypatch.setitem(
        known_implementations,
        "couldexist",
        {"class": "unimportable.CouldExist", "err": err_mgs},
    )
    with pytest.raises(ImportError) as e:
        read_csv("couldexist://test/test.csv")
        assert err_mgs in str(e.value)

def test_to_csv(cleared_fs):
    df1.to_csv("memory://test/test.csv", index=True)
    df2 = read_csv("memory://test/test.csv", parse_dates=["dt"], index_col=0)

tm.assert_frame_equal(df1, df2)

@td.skip_if_no("fastparquet")
def test_to_parquet_new_file(monkeypatch, cleared_fs):
    """Regression test for writing to a not-yet-existent GCS Parquet file."""
    df1.to_parquet(
        "memory://test/test.csv", index=True, engine="fastparquet", compression=None
    )

@td.skip_if_no("s3fs")
def test_from_s3_csv(s3_resource, tips_file):
    tm.assert_equal(read_csv("s3://pandas-test/tips.csv"), read_csv(tips_file))
    # the following are decompressed by pandas, not fsspec
    tm.assert_equal(read_csv("s3://pandas-test/tips.csv.gz"), read_csv(tips_file))
    tm.assert_equal(read_csv("s3://pandas-test/tips.csv.bz2"), read_csv(tips_file))

@pytest.mark.parametrize("protocol", ["s3", "s3a", "s3n"])
@td.skip_if_no("s3fs")
def test_s3_protocols(s3_resource, tips_file, protocol):
    tm.assert_equal(
        read_csv("%s://pandas-test/tips.csv" % protocol), read_csv(tips_file)
    )

@td.skip_if_no("s3fs")
@td.skip_if_no("fastparquet")
def test_s3_parquet(s3_resource):
    fn = "s3://pandas-test/test.parquet"
    df1.to_parquet(fn, index=False, engine="fastparquet", compression=None)
    df2 = read_parquet(fn, engine="fastparquet")
    tm.assert_equal(df1, df2)

@td.skip_if_installed("fsspec")
def test_not_present_exception():
    with pytest.raises(ImportError) as e:
        read_csv("memory://test/test.csv")
        assert "fsspec library is required" in str(e.value)

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