如何识别 Pandas 的 Parquet 后端
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How to identify Pandas' backend for Parquet
提问by Cedric H.
I understand that Pandas can read and write to and from Parquet files using different backends: pyarrowand fastparquet.
我知道 Pandas 可以使用不同的后端读写 Parquet 文件：pyarrow和fastparquet.
I have a Conda distribution with the Intel distribution and "it works": I can use pandas.DataFrame.to_parquet. However I do not have pyarrowinstalled so I guess that fastparquetis used (which I cannot find either).
我有一个带有 Intel 发行版的 Conda 发行版并且“它有效”：我可以使用pandas.DataFrame.to_parquet. 但是我没有pyarrow安装，所以我想它fastparquet被使用了（我也找不到）。
Is there a way to identify which backend is used?
有没有办法确定使用哪个后端？
采纳答案by EdChum
One method would be to call show_versions()which will list the dependencies (plus other environment stuff):
一种方法是调用show_versions()which 将列出依赖项（以及其他环境内容）：
pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 42 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.23.0
pytest: 3.0.5
pip: 9.0.3
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: 0.9999999
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
Here incidentally I don't have either pyarrowor fastparquetinstalled
这里顺便说一句，我没有任何pyarrow或fastparquet安装
Actually you can call pd.io.parquet.get_engine('auto'):
其实你可以打电话pd.io.parquet.get_engine('auto')：
In[193]:
pd.io.parquet.get_engine('auto')
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-193-929185e5aca8> in <module>()
----> 1 pd.io.parquet.get_engine('auto')
C:\ProgramData\Anaconda3\lib\site-packages\pandas\io\parquet.py in get_engine(engine)
27 pass
28
---> 29 raise ImportError("Unable to find a usable engine; "
30 "tried using: 'pyarrow', 'fastparquet'.\n"
31 "pyarrow or fastparquet is required for parquet "
ImportError: Unable to find a usable engine; tried using: 'pyarrow', 'fastparquet'.
pyarrow or fastparquet is required for parquet support
As I don't have either installed this raises an ImportError, presumably on your environment this will actually return the installed engine
由于我没有安装这会引发导入错误，大概在您的环境中这实际上会返回已安装的引擎
And after installing fastparquetI now get:
安装后fastparquet我现在得到：
In[194]:
pd.io.parquet.get_engine('auto')
Out[194]: <pandas.io.parquet.FastParquetImpl at 0xf5582b0>
And if we look at the class:
如果我们看一下class：
In[202]:
impl = pd.io.parquet.get_engine('auto')
impl.__class__
Out[202]: pandas.io.parquet.FastParquetImpl
it tells us which impl it is.
它告诉我们它是哪个 impl。
If pyarrowis installed one would get:
如果pyarrow安装了一个会得到：
>>> pd.io.parquet.get_engine('auto')
<pandas.io.parquet.PyArrowImpl object at 0xa13fb1ef0>
>>> pd.io.parquet.get_engine('auto').__class__
<class 'pandas.io.parquet.PyArrowImpl'>
回答by ANKIT CHOPADE
Just execute these 2 commands in linux shell/bash
只需在 linux shell/bash 中执行这 2 个命令
pip install pyarrow
pip install fastparquet
