一种方法是调用show_versions()
,它将列出依赖项(以及其他环境信息):
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
这里顺便提一下,我没有安装pyarrow
或fastparquet
实际上你可以调用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
由于我没有安装这两个库,因此会导致ImportError错误。在您的环境中,可能会返回已安装的引擎。
在安装了fastparquet
之后,现在我得到了以下结果:
In[194]:
pd.io.parquet.get_engine('auto')
Out[194]: <pandas.io.parquet.FastParquetImpl at 0xf5582b0>
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
它告诉我们是哪个实现。
如果安装了pyarrow
,则会得到:
>>> 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'>