You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
320 lines
9.4 KiB
320 lines
9.4 KiB
1 year ago
|
import io
|
||
|
|
||
|
import numpy as np
|
||
|
import pytest
|
||
|
|
||
|
from pandas import (
|
||
|
DataFrame,
|
||
|
date_range,
|
||
|
read_csv,
|
||
|
read_excel,
|
||
|
read_feather,
|
||
|
read_json,
|
||
|
read_parquet,
|
||
|
read_pickle,
|
||
|
read_stata,
|
||
|
read_table,
|
||
|
)
|
||
|
import pandas._testing as tm
|
||
|
from pandas.util import _test_decorators as td
|
||
|
|
||
|
|
||
|
@pytest.fixture
|
||
|
def df1():
|
||
|
return DataFrame(
|
||
|
{
|
||
|
"int": [1, 3],
|
||
|
"float": [2.0, np.nan],
|
||
|
"str": ["t", "s"],
|
||
|
"dt": date_range("2018-06-18", periods=2),
|
||
|
}
|
||
|
)
|
||
|
|
||
|
|
||
|
@pytest.fixture
|
||
|
def cleared_fs():
|
||
|
fsspec = pytest.importorskip("fsspec")
|
||
|
|
||
|
memfs = fsspec.filesystem("memory")
|
||
|
yield memfs
|
||
|
memfs.store.clear()
|
||
|
|
||
|
|
||
|
def test_read_csv(cleared_fs, df1):
|
||
|
text = str(df1.to_csv(index=False)).encode()
|
||
|
with cleared_fs.open("test/test.csv", "wb") as w:
|
||
|
w.write(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.registry import known_implementations
|
||
|
|
||
|
with pytest.raises(ValueError, match="nosuchprotocol"):
|
||
|
read_csv("nosuchprotocol://test/test.csv")
|
||
|
err_msg = "test error message"
|
||
|
monkeypatch.setitem(
|
||
|
known_implementations,
|
||
|
"couldexist",
|
||
|
{"class": "unimportable.CouldExist", "err": err_msg},
|
||
|
)
|
||
|
with pytest.raises(ImportError, match=err_msg):
|
||
|
read_csv("couldexist://test/test.csv")
|
||
|
|
||
|
|
||
|
def test_to_csv(cleared_fs, df1):
|
||
|
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)
|
||
|
|
||
|
|
||
|
def test_to_excel(cleared_fs, df1):
|
||
|
pytest.importorskip("openpyxl")
|
||
|
ext = "xlsx"
|
||
|
path = f"memory://test/test.{ext}"
|
||
|
df1.to_excel(path, index=True)
|
||
|
|
||
|
df2 = read_excel(path, parse_dates=["dt"], index_col=0)
|
||
|
|
||
|
tm.assert_frame_equal(df1, df2)
|
||
|
|
||
|
|
||
|
@pytest.mark.parametrize("binary_mode", [False, True])
|
||
|
def test_to_csv_fsspec_object(cleared_fs, binary_mode, df1):
|
||
|
fsspec = pytest.importorskip("fsspec")
|
||
|
|
||
|
path = "memory://test/test.csv"
|
||
|
mode = "wb" if binary_mode else "w"
|
||
|
with fsspec.open(path, mode=mode).open() as fsspec_object:
|
||
|
df1.to_csv(fsspec_object, index=True)
|
||
|
assert not fsspec_object.closed
|
||
|
|
||
|
mode = mode.replace("w", "r")
|
||
|
with fsspec.open(path, mode=mode) as fsspec_object:
|
||
|
df2 = read_csv(
|
||
|
fsspec_object,
|
||
|
parse_dates=["dt"],
|
||
|
index_col=0,
|
||
|
)
|
||
|
assert not fsspec_object.closed
|
||
|
|
||
|
tm.assert_frame_equal(df1, df2)
|
||
|
|
||
|
|
||
|
def test_csv_options(fsspectest):
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_csv(
|
||
|
"testmem://test/test.csv", storage_options={"test": "csv_write"}, index=False
|
||
|
)
|
||
|
assert fsspectest.test[0] == "csv_write"
|
||
|
read_csv("testmem://test/test.csv", storage_options={"test": "csv_read"})
|
||
|
assert fsspectest.test[0] == "csv_read"
|
||
|
|
||
|
|
||
|
def test_read_table_options(fsspectest):
|
||
|
# GH #39167
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_csv(
|
||
|
"testmem://test/test.csv", storage_options={"test": "csv_write"}, index=False
|
||
|
)
|
||
|
assert fsspectest.test[0] == "csv_write"
|
||
|
read_table("testmem://test/test.csv", storage_options={"test": "csv_read"})
|
||
|
assert fsspectest.test[0] == "csv_read"
|
||
|
|
||
|
|
||
|
def test_excel_options(fsspectest):
|
||
|
pytest.importorskip("openpyxl")
|
||
|
extension = "xlsx"
|
||
|
|
||
|
df = DataFrame({"a": [0]})
|
||
|
|
||
|
path = f"testmem://test/test.{extension}"
|
||
|
|
||
|
df.to_excel(path, storage_options={"test": "write"}, index=False)
|
||
|
assert fsspectest.test[0] == "write"
|
||
|
read_excel(path, storage_options={"test": "read"})
|
||
|
assert fsspectest.test[0] == "read"
|
||
|
|
||
|
|
||
|
def test_to_parquet_new_file(cleared_fs, df1):
|
||
|
"""Regression test for writing to a not-yet-existent GCS Parquet file."""
|
||
|
pytest.importorskip("fastparquet")
|
||
|
|
||
|
df1.to_parquet(
|
||
|
"memory://test/test.csv", index=True, engine="fastparquet", compression=None
|
||
|
)
|
||
|
|
||
|
|
||
|
def test_arrowparquet_options(fsspectest):
|
||
|
"""Regression test for writing to a not-yet-existent GCS Parquet file."""
|
||
|
pytest.importorskip("pyarrow")
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_parquet(
|
||
|
"testmem://test/test.csv",
|
||
|
engine="pyarrow",
|
||
|
compression=None,
|
||
|
storage_options={"test": "parquet_write"},
|
||
|
)
|
||
|
assert fsspectest.test[0] == "parquet_write"
|
||
|
read_parquet(
|
||
|
"testmem://test/test.csv",
|
||
|
engine="pyarrow",
|
||
|
storage_options={"test": "parquet_read"},
|
||
|
)
|
||
|
assert fsspectest.test[0] == "parquet_read"
|
||
|
|
||
|
|
||
|
@td.skip_array_manager_not_yet_implemented # TODO(ArrayManager) fastparquet
|
||
|
def test_fastparquet_options(fsspectest):
|
||
|
"""Regression test for writing to a not-yet-existent GCS Parquet file."""
|
||
|
pytest.importorskip("fastparquet")
|
||
|
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_parquet(
|
||
|
"testmem://test/test.csv",
|
||
|
engine="fastparquet",
|
||
|
compression=None,
|
||
|
storage_options={"test": "parquet_write"},
|
||
|
)
|
||
|
assert fsspectest.test[0] == "parquet_write"
|
||
|
read_parquet(
|
||
|
"testmem://test/test.csv",
|
||
|
engine="fastparquet",
|
||
|
storage_options={"test": "parquet_read"},
|
||
|
)
|
||
|
assert fsspectest.test[0] == "parquet_read"
|
||
|
|
||
|
|
||
|
@pytest.mark.single_cpu
|
||
|
def test_from_s3_csv(s3_public_bucket_with_data, tips_file, s3so):
|
||
|
pytest.importorskip("s3fs")
|
||
|
tm.assert_equal(
|
||
|
read_csv(
|
||
|
f"s3://{s3_public_bucket_with_data.name}/tips.csv", storage_options=s3so
|
||
|
),
|
||
|
read_csv(tips_file),
|
||
|
)
|
||
|
# the following are decompressed by pandas, not fsspec
|
||
|
tm.assert_equal(
|
||
|
read_csv(
|
||
|
f"s3://{s3_public_bucket_with_data.name}/tips.csv.gz", storage_options=s3so
|
||
|
),
|
||
|
read_csv(tips_file),
|
||
|
)
|
||
|
tm.assert_equal(
|
||
|
read_csv(
|
||
|
f"s3://{s3_public_bucket_with_data.name}/tips.csv.bz2", storage_options=s3so
|
||
|
),
|
||
|
read_csv(tips_file),
|
||
|
)
|
||
|
|
||
|
|
||
|
@pytest.mark.single_cpu
|
||
|
@pytest.mark.parametrize("protocol", ["s3", "s3a", "s3n"])
|
||
|
def test_s3_protocols(s3_public_bucket_with_data, tips_file, protocol, s3so):
|
||
|
pytest.importorskip("s3fs")
|
||
|
tm.assert_equal(
|
||
|
read_csv(
|
||
|
f"{protocol}://{s3_public_bucket_with_data.name}/tips.csv",
|
||
|
storage_options=s3so,
|
||
|
),
|
||
|
read_csv(tips_file),
|
||
|
)
|
||
|
|
||
|
|
||
|
@pytest.mark.single_cpu
|
||
|
@td.skip_array_manager_not_yet_implemented # TODO(ArrayManager) fastparquet
|
||
|
def test_s3_parquet(s3_public_bucket, s3so, df1):
|
||
|
pytest.importorskip("fastparquet")
|
||
|
pytest.importorskip("s3fs")
|
||
|
|
||
|
fn = f"s3://{s3_public_bucket.name}/test.parquet"
|
||
|
df1.to_parquet(
|
||
|
fn, index=False, engine="fastparquet", compression=None, storage_options=s3so
|
||
|
)
|
||
|
df2 = read_parquet(fn, engine="fastparquet", storage_options=s3so)
|
||
|
tm.assert_equal(df1, df2)
|
||
|
|
||
|
|
||
|
@td.skip_if_installed("fsspec")
|
||
|
def test_not_present_exception():
|
||
|
msg = "Missing optional dependency 'fsspec'|fsspec library is required"
|
||
|
with pytest.raises(ImportError, match=msg):
|
||
|
read_csv("memory://test/test.csv")
|
||
|
|
||
|
|
||
|
def test_feather_options(fsspectest):
|
||
|
pytest.importorskip("pyarrow")
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_feather("testmem://mockfile", storage_options={"test": "feather_write"})
|
||
|
assert fsspectest.test[0] == "feather_write"
|
||
|
out = read_feather("testmem://mockfile", storage_options={"test": "feather_read"})
|
||
|
assert fsspectest.test[0] == "feather_read"
|
||
|
tm.assert_frame_equal(df, out)
|
||
|
|
||
|
|
||
|
def test_pickle_options(fsspectest):
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_pickle("testmem://mockfile", storage_options={"test": "pickle_write"})
|
||
|
assert fsspectest.test[0] == "pickle_write"
|
||
|
out = read_pickle("testmem://mockfile", storage_options={"test": "pickle_read"})
|
||
|
assert fsspectest.test[0] == "pickle_read"
|
||
|
tm.assert_frame_equal(df, out)
|
||
|
|
||
|
|
||
|
def test_json_options(fsspectest, compression):
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_json(
|
||
|
"testmem://mockfile",
|
||
|
compression=compression,
|
||
|
storage_options={"test": "json_write"},
|
||
|
)
|
||
|
assert fsspectest.test[0] == "json_write"
|
||
|
out = read_json(
|
||
|
"testmem://mockfile",
|
||
|
compression=compression,
|
||
|
storage_options={"test": "json_read"},
|
||
|
)
|
||
|
assert fsspectest.test[0] == "json_read"
|
||
|
tm.assert_frame_equal(df, out)
|
||
|
|
||
|
|
||
|
def test_stata_options(fsspectest):
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_stata(
|
||
|
"testmem://mockfile", storage_options={"test": "stata_write"}, write_index=False
|
||
|
)
|
||
|
assert fsspectest.test[0] == "stata_write"
|
||
|
out = read_stata("testmem://mockfile", storage_options={"test": "stata_read"})
|
||
|
assert fsspectest.test[0] == "stata_read"
|
||
|
tm.assert_frame_equal(df, out.astype("int64"))
|
||
|
|
||
|
|
||
|
def test_markdown_options(fsspectest):
|
||
|
pytest.importorskip("tabulate")
|
||
|
df = DataFrame({"a": [0]})
|
||
|
df.to_markdown("testmem://mockfile", storage_options={"test": "md_write"})
|
||
|
assert fsspectest.test[0] == "md_write"
|
||
|
assert fsspectest.cat("testmem://mockfile")
|
||
|
|
||
|
|
||
|
def test_non_fsspec_options():
|
||
|
pytest.importorskip("pyarrow")
|
||
|
with pytest.raises(ValueError, match="storage_options"):
|
||
|
read_csv("localfile", storage_options={"a": True})
|
||
|
with pytest.raises(ValueError, match="storage_options"):
|
||
|
# separate test for parquet, which has a different code path
|
||
|
read_parquet("localfile", storage_options={"a": True})
|
||
|
by = io.BytesIO()
|
||
|
|
||
|
with pytest.raises(ValueError, match="storage_options"):
|
||
|
read_csv(by, storage_options={"a": True})
|
||
|
|
||
|
df = DataFrame({"a": [0]})
|
||
|
with pytest.raises(ValueError, match="storage_options"):
|
||
|
df.to_parquet("nonfsspecpath", storage_options={"a": True})
|