TST: Test_parquet failing

[RjLi13]

Code Sample, a copy-pastable example if possible

pytest -x pandas
...
============================================= FAILURES =============================================
_____________________________________ test_cross_engine_pa_fp ______________________________________
[gw0] darwin -- Python 3.7.1 /Users/ruijing/anaconda3/envs/pandas-dev/bin/python
[XPASS(strict)] reading pa metadata failing on Windows/mac
...
=== 1 failed, 44359 passed, 1104 skipped, 962 xfailed, 16 xpassed, 76 warnings in 601.05 seconds ===

@pytest.mark.xfail(is_platform_windows() or is_platform_mac(),
                   reason="reading pa metadata failing on Windows/mac")
def test_cross_engine_pa_fp(df_cross_compat, pa, fp):

Problem description

Building the development environment of pandas from latest master source, and then running the pytest suite on a fresh install with no changes, leads to test_cross_engine_pa_fp test in test_parquet.py, which is expected to fail, passing. This could be due to the fact that either Python 3.7 or OS X 10.14 now supports what this test is testing for, cross-compat with differing reading/writing engines. Since this is the case, loosening the strictness of this test, per @TomAugspurger suggestion, should fix this. I can open up a pr for this.

Expected Output

Unit tests should not report failures

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line]
INSTALLED VERSIONS

commit: 80295f9
python: 3.7.1.final.0
python-bits: 64
OS: Darwin
OS-release: 18.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.0.dev0+1398.g80295f948
pytest: 4.0.2
pip: 18.1
setuptools: 40.6.3
Cython: 0.29.2
numpy: 1.15.4
scipy: 1.1.0
pyarrow: 0.11.1
xarray: 0.11.0
IPython: 7.2.0
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.2
openpyxl: 2.5.12
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml.etree: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: 0.2.0
fastparquet: 0.1.6
pandas_gbq: None
pandas_datareader: None
gcsfs: None