pip安装pyarrow后在jupyter笔记本中导入pyarrow时出错

Question

我在将pyarrow导入我的jupyter笔记本时遇到问题。为了提供一些上下文，我创建了一个名为rc_env的虚拟环境。我已经多次卸载并重新安装pyarrow，但这是我最近安装Pyarow时收到的消息

pip install pyarrow
Requirement already satisfied: pyarrow in ./Environments/rc_env/lib/python3.8/site-packages (4.0.1)
Requirement already satisfied: numpy>=1.16.6 in ./Environments/rc_env/lib/python3.8/site-packages (from pyarrow) (1.21.0)

所以包在我的环境中。对于另一个合理性检查，我使用pip list命令查看安装在我的环境中的python包

(rc_env) LTA00015JFK:~ adenner$ pip list
Package                       Version
----------------------------- ---------
appnope                       0.1.2
argon2-cffi                   20.1.0
async-generator               1.10
attrs                         21.2.0
backcall                      0.2.0
beautifulsoup4                4.9.3
bleach                        3.3.0
boto3                         1.17.103
botocore                      1.20.103
cachetools                    4.2.2
certifi                       2021.5.30
cffi                          1.14.5
chardet                       4.0.0
cycler                        0.10.0
debugpy                       1.3.0
decorator                     5.0.9
defusedxml                    0.7.1
dictor                        0.1.7
entrypoints                   0.3
et-xmlfile                    1.1.0
google                        3.0.0
google-api-core               1.30.0
google-api-python-client      2.11.0
google-auth                   1.32.1
google-auth-httplib2          0.1.0
google-auth-oauthlib          0.4.4
google-cloud                  0.34.0
google-cloud-bigquery         2.20.0
google-cloud-bigquery-storage 2.5.0
google-cloud-core             1.7.1
google-cloud-vision           2.3.2
google-crc32c                 1.1.2
google-resumable-media        1.3.1
googleapis-common-protos      1.53.0
grpcio                        1.38.1
httplib2                      0.19.1
idna                          2.10
ipykernel                     6.0.0
ipython                       7.25.0
ipython-genutils              0.2.0
ipywidgets                    7.6.3
jedi                          0.18.0
Jinja2                        3.0.1
jmespath                      0.10.0
jsonschema                    3.2.0
jupyter                       1.0.0
jupyter-client                6.1.12
jupyter-console               6.4.0
jupyter-core                  4.7.1
jupyterlab-pygments           0.1.2
jupyterlab-widgets            1.0.0
kiwisolver                    1.3.1
libcst                        0.3.19
MarkupSafe                    2.0.1
matplotlib                    3.4.2
matplotlib-inline             0.1.2
mistune                       0.8.4
mypy-extensions               0.4.3
nbclient                      0.5.3
nbconvert                     6.1.0
nbformat                      5.1.3
nest-asyncio                  1.5.1
notebook                      6.4.0
numpy                         1.21.0
oauthlib                      3.1.1
openpyxl                      3.0.7
packaging                     20.9
pandas                        1.2.5
pandas-gbq                    0.15.0
pandocfilters                 1.4.3
parso                         0.8.2
pexpect                       4.8.0
pickleshare                   0.7.5
Pillow                        8.3.0
pip                           21.1.3
prometheus-client             0.11.0
prompt-toolkit                3.0.19
proto-plus                    1.19.0
protobuf                      3.17.3
ptyprocess                    0.7.0
pyarrow                       4.0.1
pyasn1                        0.4.8
pyasn1-modules                0.2.8
pycparser                     2.20
pydata-google-auth            1.2.0
Pygments                      2.9.0
pyparsing                     2.4.7
pyrsistent                    0.18.0
python-dateutil               2.8.1
pytz                          2021.1
PyYAML                        5.4.1
pyzmq                         22.1.0
qtconsole                     5.1.1
QtPy                          1.9.0
requests                      2.25.1
requests-oauthlib             1.3.0
rsa                           4.7.2
s3transfer                    0.4.2
scipy                         1.7.0
seaborn                       0.11.1
Send2Trash                    1.7.1
seshat                        0.8.5
setuptools                    57.0.0
six                           1.16.0
soupsieve                     2.2.1
terminado                     0.10.1
testpath                      0.5.0
titlecase                     2.2.0
tornado                       6.1
tqdm                          4.61.1
traitlets                     5.0.5
typing-extensions             3.10.0.0
typing-inspect                0.7.1
uritemplate                   3.0.1
urllib3                       1.26.6
uuid                          1.30
wcwidth                       0.2.5
webencodings                  0.5.1
wheel                         0.36.2
widgetsnbextension            3.5.1
XlsxWriter                    1.4.3

现在，当我打开python并尝试导入模块时，我收到以下错误消息：

(rc_env) LTA00015JFK:~ adenner$ python 
Python 3.8.5 (v3.8.5:580fbb018f, Jul 20 2020, 12:11:27) 
[Clang 6.0 (clang-600.0.57)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pyarrow 
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/adenner/Environments/rc_env/lib/python3.8/site-packages/pyarrow/__init__.py", line 63, in <module>
    import pyarrow.lib as _lib
ImportError: dlopen(/Users/adenner/Environments/rc_env/lib/python3.8/site-packages/pyarrow/lib.cpython-38-darwin.so, 2): Symbol not found: ____chkstk_darwin
  Referenced from: /Users/adenner/Environments/rc_env/lib/python3.8/site-packages/pyarrow/libarrow.400.dylib
  Expected in: /usr/lib/libSystem.B.dylib
 in /Users/adenner/Environments/rc_env/lib/python3.8/site-packages/pyarrow/libarrow.400.dylib

我曾尝试使用anaconda3和miniconda3环境，但不幸的是，我一直收到相同的错误消息。我也在使用macOS High Serra版本10.13.6。有什么建议吗

Answer 1

这是最新版本pyarrow的已知错误：https://issues.apache.org/jira/browse/ARROW-13108。您将需要macOS 10.15+来运行轮子构建

由于您已经处于由conda创建的环境中，因此可以改用pyarrowconda包。这将在macOS 10.9+上运行，甚至是安装pyarrow的首选方式：

conda install -c conda-forge pyarrow

或者使用mamba：

mamba install -c conda-forge pyarrow

Answer 2

您可以尝试使用jupyter lab而不是使用jupyter笔记本。我在使用笔记本电脑时遇到了这个问题，但pyarrow在jupyter实验室工作得很好