299 lines
9.5 KiB
Python
299 lines
9.5 KiB
Python
from io import StringIO
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
|
|
import pandas as pd
|
|
from pandas import (
|
|
DataFrame,
|
|
read_json,
|
|
)
|
|
import pandas._testing as tm
|
|
|
|
from pandas.io.json._json import JsonReader
|
|
|
|
|
|
@pytest.fixture
|
|
def lines_json_df():
|
|
df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
|
|
return df.to_json(lines=True, orient="records")
|
|
|
|
|
|
def test_read_jsonl():
|
|
# GH9180
|
|
result = read_json('{"a": 1, "b": 2}\n{"b":2, "a" :1}\n', lines=True)
|
|
expected = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
def test_read_datetime():
|
|
# GH33787
|
|
df = DataFrame(
|
|
[([1, 2], ["2020-03-05", "2020-04-08T09:58:49+00:00"], "hector")],
|
|
columns=["accounts", "date", "name"],
|
|
)
|
|
json_line = df.to_json(lines=True, orient="records")
|
|
result = read_json(json_line)
|
|
expected = DataFrame(
|
|
[[1, "2020-03-05", "hector"], [2, "2020-04-08T09:58:49+00:00", "hector"]],
|
|
columns=["accounts", "date", "name"],
|
|
)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
def test_read_jsonl_unicode_chars():
|
|
# GH15132: non-ascii unicode characters
|
|
# \u201d == RIGHT DOUBLE QUOTATION MARK
|
|
|
|
# simulate file handle
|
|
json = '{"a": "foo”", "b": "bar"}\n{"a": "foo", "b": "bar"}\n'
|
|
json = StringIO(json)
|
|
result = read_json(json, lines=True)
|
|
expected = DataFrame([["foo\u201d", "bar"], ["foo", "bar"]], columns=["a", "b"])
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# simulate string
|
|
json = '{"a": "foo”", "b": "bar"}\n{"a": "foo", "b": "bar"}\n'
|
|
result = read_json(json, lines=True)
|
|
expected = DataFrame([["foo\u201d", "bar"], ["foo", "bar"]], columns=["a", "b"])
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
def test_to_jsonl():
|
|
# GH9180
|
|
df = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])
|
|
result = df.to_json(orient="records", lines=True)
|
|
expected = '{"a":1,"b":2}\n{"a":1,"b":2}\n'
|
|
assert result == expected
|
|
|
|
df = DataFrame([["foo}", "bar"], ['foo"', "bar"]], columns=["a", "b"])
|
|
result = df.to_json(orient="records", lines=True)
|
|
expected = '{"a":"foo}","b":"bar"}\n{"a":"foo\\"","b":"bar"}\n'
|
|
assert result == expected
|
|
tm.assert_frame_equal(read_json(result, lines=True), df)
|
|
|
|
# GH15096: escaped characters in columns and data
|
|
df = DataFrame([["foo\\", "bar"], ['foo"', "bar"]], columns=["a\\", "b"])
|
|
result = df.to_json(orient="records", lines=True)
|
|
expected = '{"a\\\\":"foo\\\\","b":"bar"}\n{"a\\\\":"foo\\"","b":"bar"}\n'
|
|
assert result == expected
|
|
tm.assert_frame_equal(read_json(result, lines=True), df)
|
|
|
|
|
|
def test_to_jsonl_count_new_lines():
|
|
# GH36888
|
|
df = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])
|
|
actual_new_lines_count = df.to_json(orient="records", lines=True).count("\n")
|
|
expected_new_lines_count = 2
|
|
assert actual_new_lines_count == expected_new_lines_count
|
|
|
|
|
|
@pytest.mark.parametrize("chunksize", [1, 1.0])
|
|
def test_readjson_chunks(lines_json_df, chunksize):
|
|
# Basic test that read_json(chunks=True) gives the same result as
|
|
# read_json(chunks=False)
|
|
# GH17048: memory usage when lines=True
|
|
|
|
unchunked = read_json(StringIO(lines_json_df), lines=True)
|
|
with read_json(StringIO(lines_json_df), lines=True, chunksize=chunksize) as reader:
|
|
chunked = pd.concat(reader)
|
|
|
|
tm.assert_frame_equal(chunked, unchunked)
|
|
|
|
|
|
def test_readjson_chunksize_requires_lines(lines_json_df):
|
|
msg = "chunksize can only be passed if lines=True"
|
|
with pytest.raises(ValueError, match=msg):
|
|
with read_json(StringIO(lines_json_df), lines=False, chunksize=2) as _:
|
|
pass
|
|
|
|
|
|
def test_readjson_chunks_series():
|
|
# Test reading line-format JSON to Series with chunksize param
|
|
s = pd.Series({"A": 1, "B": 2})
|
|
|
|
strio = StringIO(s.to_json(lines=True, orient="records"))
|
|
unchunked = read_json(strio, lines=True, typ="Series")
|
|
|
|
strio = StringIO(s.to_json(lines=True, orient="records"))
|
|
with read_json(strio, lines=True, typ="Series", chunksize=1) as reader:
|
|
chunked = pd.concat(reader)
|
|
|
|
tm.assert_series_equal(chunked, unchunked)
|
|
|
|
|
|
def test_readjson_each_chunk(lines_json_df):
|
|
# Other tests check that the final result of read_json(chunksize=True)
|
|
# is correct. This checks the intermediate chunks.
|
|
with read_json(StringIO(lines_json_df), lines=True, chunksize=2) as reader:
|
|
chunks = list(reader)
|
|
assert chunks[0].shape == (2, 2)
|
|
assert chunks[1].shape == (1, 2)
|
|
|
|
|
|
def test_readjson_chunks_from_file():
|
|
with tm.ensure_clean("test.json") as path:
|
|
df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
|
|
df.to_json(path, lines=True, orient="records")
|
|
with read_json(path, lines=True, chunksize=1) as reader:
|
|
chunked = pd.concat(reader)
|
|
unchunked = read_json(path, lines=True)
|
|
tm.assert_frame_equal(unchunked, chunked)
|
|
|
|
|
|
@pytest.mark.parametrize("chunksize", [None, 1])
|
|
def test_readjson_chunks_closes(chunksize):
|
|
with tm.ensure_clean("test.json") as path:
|
|
df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
|
|
df.to_json(path, lines=True, orient="records")
|
|
reader = JsonReader(
|
|
path,
|
|
orient=None,
|
|
typ="frame",
|
|
dtype=True,
|
|
convert_axes=True,
|
|
convert_dates=True,
|
|
keep_default_dates=True,
|
|
numpy=False,
|
|
precise_float=False,
|
|
date_unit=None,
|
|
encoding=None,
|
|
lines=True,
|
|
chunksize=chunksize,
|
|
compression=None,
|
|
nrows=None,
|
|
)
|
|
with reader:
|
|
reader.read()
|
|
assert (
|
|
reader.handles.handle.closed
|
|
), f"didn't close stream with chunksize = {chunksize}"
|
|
|
|
|
|
@pytest.mark.parametrize("chunksize", [0, -1, 2.2, "foo"])
|
|
def test_readjson_invalid_chunksize(lines_json_df, chunksize):
|
|
msg = r"'chunksize' must be an integer >=1"
|
|
|
|
with pytest.raises(ValueError, match=msg):
|
|
with read_json(StringIO(lines_json_df), lines=True, chunksize=chunksize) as _:
|
|
pass
|
|
|
|
|
|
@pytest.mark.parametrize("chunksize", [None, 1, 2])
|
|
def test_readjson_chunks_multiple_empty_lines(chunksize):
|
|
j = """
|
|
|
|
{"A":1,"B":4}
|
|
|
|
|
|
|
|
{"A":2,"B":5}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
{"A":3,"B":6}
|
|
"""
|
|
orig = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
|
|
test = read_json(j, lines=True, chunksize=chunksize)
|
|
if chunksize is not None:
|
|
with test:
|
|
test = pd.concat(test)
|
|
tm.assert_frame_equal(orig, test, obj=f"chunksize: {chunksize}")
|
|
|
|
|
|
def test_readjson_unicode(monkeypatch):
|
|
with tm.ensure_clean("test.json") as path:
|
|
monkeypatch.setattr("locale.getpreferredencoding", lambda l: "cp949")
|
|
with open(path, "w", encoding="utf-8") as f:
|
|
f.write('{"£©µÀÆÖÞßéöÿ":["АБВГДабвгд가"]}')
|
|
|
|
result = read_json(path)
|
|
expected = DataFrame({"£©µÀÆÖÞßéöÿ": ["АБВГДабвгд가"]})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize("nrows", [1, 2])
|
|
def test_readjson_nrows(nrows):
|
|
# GH 33916
|
|
# Test reading line-format JSON to Series with nrows param
|
|
jsonl = """{"a": 1, "b": 2}
|
|
{"a": 3, "b": 4}
|
|
{"a": 5, "b": 6}
|
|
{"a": 7, "b": 8}"""
|
|
result = read_json(jsonl, lines=True, nrows=nrows)
|
|
expected = DataFrame({"a": [1, 3, 5, 7], "b": [2, 4, 6, 8]}).iloc[:nrows]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize("nrows,chunksize", [(2, 2), (4, 2)])
|
|
def test_readjson_nrows_chunks(nrows, chunksize):
|
|
# GH 33916
|
|
# Test reading line-format JSON to Series with nrows and chunksize param
|
|
jsonl = """{"a": 1, "b": 2}
|
|
{"a": 3, "b": 4}
|
|
{"a": 5, "b": 6}
|
|
{"a": 7, "b": 8}"""
|
|
with read_json(jsonl, lines=True, nrows=nrows, chunksize=chunksize) as reader:
|
|
chunked = pd.concat(reader)
|
|
expected = DataFrame({"a": [1, 3, 5, 7], "b": [2, 4, 6, 8]}).iloc[:nrows]
|
|
tm.assert_frame_equal(chunked, expected)
|
|
|
|
|
|
def test_readjson_nrows_requires_lines():
|
|
# GH 33916
|
|
# Test ValuError raised if nrows is set without setting lines in read_json
|
|
jsonl = """{"a": 1, "b": 2}
|
|
{"a": 3, "b": 4}
|
|
{"a": 5, "b": 6}
|
|
{"a": 7, "b": 8}"""
|
|
msg = "nrows can only be passed if lines=True"
|
|
with pytest.raises(ValueError, match=msg):
|
|
read_json(jsonl, lines=False, nrows=2)
|
|
|
|
|
|
def test_readjson_lines_chunks_fileurl(datapath):
|
|
# GH 27135
|
|
# Test reading line-format JSON from file url
|
|
df_list_expected = [
|
|
DataFrame([[1, 2]], columns=["a", "b"], index=[0]),
|
|
DataFrame([[3, 4]], columns=["a", "b"], index=[1]),
|
|
DataFrame([[5, 6]], columns=["a", "b"], index=[2]),
|
|
]
|
|
os_path = datapath("io", "json", "data", "line_delimited.json")
|
|
file_url = Path(os_path).as_uri()
|
|
with read_json(file_url, lines=True, chunksize=1) as url_reader:
|
|
for index, chuck in enumerate(url_reader):
|
|
tm.assert_frame_equal(chuck, df_list_expected[index])
|
|
|
|
|
|
def test_chunksize_is_incremental():
|
|
# See https://github.com/pandas-dev/pandas/issues/34548
|
|
jsonl = (
|
|
"""{"a": 1, "b": 2}
|
|
{"a": 3, "b": 4}
|
|
{"a": 5, "b": 6}
|
|
{"a": 7, "b": 8}\n"""
|
|
* 1000
|
|
)
|
|
|
|
class MyReader:
|
|
def __init__(self, contents):
|
|
self.read_count = 0
|
|
self.stringio = StringIO(contents)
|
|
|
|
def read(self, *args):
|
|
self.read_count += 1
|
|
return self.stringio.read(*args)
|
|
|
|
def __iter__(self):
|
|
self.read_count += 1
|
|
return iter(self.stringio)
|
|
|
|
reader = MyReader(jsonl)
|
|
assert len(list(read_json(reader, lines=True, chunksize=100))) > 1
|
|
assert reader.read_count > 10
|