在make html或sphinx-apidoc期间没有错误。
但是
sphinx-build -b html ./rst/ ./html/
我得到：
WARNING: autodoc: failed to import module u'mcp.mcp.ann_mcp'; the following exception was raised: No module named mcp.ann_mcp
在config.py中，我添加了：
import os
import sys
sys.path.append('/home/neurodad/source')
sys.path.append('/home/neurodad/source/mcp')
sys.path.append('/home/neurodad/source/mcp/mcp')
print "PATH:", sys.path
和sys.path的打印输出给我：
PATH: ['/home/neurodad/miniconda2/envs/prod_keras/bin', '/home/neurodad/miniconda2/envs/prod_keras/lib/python27.zip', '/home/neurodad/miniconda2/envs/prod_keras/lib/python2.7', '/home/neurodad/miniconda2/envs/prod_keras/lib/python2.7/plat-linux2', '/home/neurodad/miniconda2/envs/prod_keras/lib/python2.7/lib-tk', '/home/neurodad/miniconda2/envs/prod_keras/lib/python2.7/lib-old', '/home/neurodad/miniconda2/envs/prod_keras/lib/python2.7/lib-dynload', '/home/neurodad/miniconda2/envs/prod_keras/lib/python2.7/site-packages', '/home/neurodad/source/outlierdetector', '/home/neurodad/source/databalancer', '/home/neurodad/source/datanexus', '/home/neurodad/source/distributiontransformer', '/home/neurodad/source/mcp', '/home/neurodad/source/optimization', '/home/neurodad/source/setmaker', '/home/neurodad/source/zswtools', '/home/neurodad/source/supervisedlearning', '/home/neurodad/source', '/home/neurodad/source', '/home/neurodad/source/mcp', '/home/neurodad/source/mcp/mcp']
我搜索了网络，但是每个与我的问题有关的技巧都是“将源路径添加到您的conf.py”。 我没主意-希望您能提供帮助。 非常感谢！
更新： 我做了最少的代码：
class dummy(object):
def __init__(self, d1):
self.d1 = d1
def dummy_method(self, d2):
"""
Args:
d2 (str): second test string.
Example:
'>>> my_dummy = dummy("Hello World!")'
'>>> my_dummy.dummy_method("Hello Back.")'
Hello World! Hello Back.
"""
print self.d1, d2
if __name__ == '__main__':
my_dummy = dummy("Hello World!")
my_dummy.dummy_method("Hello Back.")
conda软件包列表在这里：
# Name Version Build Channel
_tflow_190_select 0.0.1 gpu
absl-py 0.3.0 py27_0
alabaster 0.7.11 py27_0
asn1crypto 0.24.0 py27_0
astor 0.7.1 py27_0
attrdict 2.0.0 py_1 conda-forge
babel 2.6.0 py27_0
backports 1.0 py27_1
backports.functools_lru_cache 1.5 py27_1
backports.weakref 1.0.post1 py27_0
backports_abc 0.5 py27_0
beautifulsoup4 4.6.1 py27_0
blas 1.0 mkl
ca-certificates 2018.03.07 0
certifi 2018.4.16 py27_0
cffi 1.11.5 py27h9745a5d_0
chardet 3.0.4 py27_1
conda 4.5.9 py27_0
conda-build 3.12.1 py27_0
conda-env 2.6.0 1
contextlib2 0.5.5 py27_0
cryptography 2.3 py27hb7f436b_0
cryptography-vectors 2.3 py27_0
cudatoolkit 9.0 h13b8566_0
cudnn 7.1.2 cuda9.0_0
cupti 9.0.176 0
cycler 0.10.0 py27hc7354d3_0
dbus 1.13.2 h714fa37_1
docutils 0.14 py27_0
enum34 1.1.6 py27_1
expat 2.2.5 he0dffb1_0
filelock 3.0.4 py27_0
fontconfig 2.13.0 h9420a91_0
freetype 2.9.1 h8a8886c_0
funcsigs 1.0.2 py27_0
functools32 3.2.3.2 py27_1
futures 3.2.0 py27_0
gast 0.2.0 py27_0
glib 2.56.1 h000015b_0
glob2 0.6 py27_0
grpcio 1.12.1 py27hdbcaa40_0
gst-plugins-base 1.14.0 hbbd80ab_1
gstreamer 1.14.0 hb453b48_1
h5py 2.8.0 py27h8d01980_0
hdf5 1.10.2 hba1933b_1
icu 58.2 h9c2bf20_1
idna 2.7 py27_0
imagesize 1.0.0 py27_0
intel-openmp 2018.0.3 0
ipaddress 1.0.22 py27_0
jinja2 2.10 py27_0
jpeg 9b h024ee3a_2
keras 2.2.2 0
keras-applications 1.0.4 py27_0
keras-base 2.2.2 py27_0
keras-preprocessing 1.0.2 py27_0
kiwisolver 1.0.1 py27hf484d3e_0
libedit 3.1.20170329 h6b74fdf_2
libffi 3.2.1 hd88cf55_4
libgcc-ng 7.2.0 hdf63c60_3
libgfortran-ng 7.2.0 hdf63c60_3
libpng 1.6.34 hb9fc6fc_0
libprotobuf 3.5.2 h6f1eeef_0
libstdcxx-ng 7.2.0 hdf63c60_3
libuuid 1.0.3 h1bed415_2
libxcb 1.13 h1bed415_1
libxml2 2.9.8 h26e45fe_1
linecache2 1.0.0 py27_0
markdown 2.6.11 py27_0
markupsafe 1.0 py27h14c3975_1
matplotlib 2.2.2 py27hb69df0a_2
mkl 2018.0.3 1
mkl_fft 1.0.4 py27h4414c95_1
mkl_random 1.0.1 py27h4414c95_1
mock 2.0.0 py27h0c0c831_0
ncurses 6.1 hf484d3e_0
numpy 1.15.0 py27h1b885b7_0
numpy-base 1.15.0 py27h3dfced4_0
openssl 1.0.2o h14c3975_1
packaging 17.1 py27_0
pandas 0.23.4 py27h04863e7_0
patchelf 0.9 hf484d3e_2
patsy 0.5.0 py27_0
pbr 4.2.0 py27_0
pcre 8.42 h439df22_0
pip 10.0.1 py27_0
pkginfo 1.4.2 py27_1
protobuf 3.5.2 py27hf484d3e_1
psutil 5.4.6 py27h14c3975_0
pycosat 0.6.3 py27h14c3975_0
pycparser 2.18 py27_1
pygments 2.2.0 py27h4a8b6f5_0
pyopenssl 18.0.0 py27_0
pyparsing 2.2.0 py27_1
pyqt 5.9.2 py27h22d08a2_0
pysocks 1.6.8 py27_0
python 2.7.15 h1571d57_0
python-dateutil 2.7.3 py27_0
pytz 2018.5 py27_0
pyyaml 3.13 py27h14c3975_0
qt 5.9.6 h52aff34_0
readline 7.0 ha6073c6_4
requests 2.19.1 py27_0
ruamel_yaml 0.15.46 py27h14c3975_0
scandir 1.8 py27h14c3975_0
scikit-learn 0.19.1 py27hedc7406_0
scipy 1.1.0 py27hc49cb51_0
seaborn 0.9.0 py27_0
setuptools 39.2.0 py27_0
singledispatch 3.4.0.3 py27_0
sip 4.19.8 py27hf484d3e_0
six 1.11.0 py27_1
snowballstemmer 1.2.1 py27_0
sphinx 1.7.6 py27_0
sphinxcontrib 1.0 py27_1
sphinxcontrib-websupport 1.1.0 py27_1
sqlite 3.24.0 h84994c4_0
statsmodels 0.9.0 py27h035aef0_0
subprocess32 3.5.2 py27h14c3975_0
tensorboard 1.9.0 py27hf484d3e_0
tensorflow 1.9.0 gpu_py27hd3a791e_1
tensorflow-base 1.9.0 gpu_py27h6ecc378_0
tensorflow-gpu 1.9.0 hf154084_0
termcolor 1.1.0 py27_1
tk 8.6.7 hc745277_3
tornado 5.0.2 py27h14c3975_0
traceback2 1.4.0 py27_0
typing 3.6.4 py27_0
unittest2 1.1.0 py27_0
urllib3 1.23 py27_0
werkzeug 0.14.1 py27_0
wheel 0.31.1 py27_0
xz 5.2.4 h14c3975_4
yaml 0.1.7 had09818_2
zlib 1.2.11 ha838bed_2
$ PATH是：
/home/neurodad/miniconda2/envs/prod_keras/bin:/home/neurodad/miniconda2/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/usr/local/cuda/bin:/usr/local/cuda/bin:/snap/bin:/usr/lib/jvm/java-8-oracle/bin:/usr/lib/jvm/java-8-oracle/db/bin:/usr/lib/jvm/java-8-oracle/jre/bin
这是完整的文件夹结构，其中包含sphinx-quickstart创建的所有文件以及经过修改的conf.py作为zip文件： https://www.dropbox.com/s/f4bvtlu8xvl7eaj/sphinx_mcve.zip?dl=0
答案 0 :(得分：0)
问题确实根源于Conda环境。 如果我停用Conda env并将所有必需的路径添加到PYTHONPATH，则狮身人面像程序可以正常工作。
我想我会朝那个方向搜索网。 感谢您的建议和帮助。