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BUG: read_parquet Google Cloud Storage (gcs) dir support #36743
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The expected syntax for multiple parquet files should probably follow the wildcard approach you can use on GCS, e.g. For example, the wildcard would be required if you were loading those files from Parquet on GCS into BigQuery. |
Still waiting for this .. |
@borislitvak this is an all volunteer project you are welcome to contribute a patch |
@borislitvak It seems to work now (with pyarrow), at least partially: It still fails when there is only one file in the directory, but this seems more of a pyarrow bug? Click to expand output of pd.show_versions()INSTALLED VERSIONScommit : 5f648bf pandas : 1.3.2 Traceback with one file only:
|
I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
(optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
Problem description
In the same vain as issue 26388, it would be nice for pandas to read multiple parquet files stored under a gcs path, in this case
gs://bucket/path
. Issue 26388 hints that this should already work in pandas 1.x.x however, I still get one of the following errorsor
Expected Output
Code runs without error.
Output of
pd.show_versions()
INSTALLED VERSIONS
commit : 2a7d332
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
Version : Darwin Kernel Version 18.7.0: Thu Jun 18 20:50:10 PDT 2020; root:xnu-4903.278.43~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.2
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.6.0.post20200917
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.3
fastparquet : None
gcsfs : 0.7.1
matplotlib : 3.3.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
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