sklearn/umap 的 ReadTheDocs 问题
ReadTheDocs trouble with sklearn/umap
我有一个我之前在 ReadTheDocs 上成功构建的包，但现在不再是这样了。我的导入如下：
import pandas as pd
import numpy as np
import scipy
import sys
from annoy import AnnoyIndex
from packaging import version
from scipy.spatial import cKDTree
from scipy.sparse import coo_matrix
from umap.umap_ import fuzzy_simplicial_set
from sklearn.neighbors import KDTree
from sklearn.neighbors import DistanceMetric
from sklearn.linear_model import Ridge
我通过在 Sphinx 中模拟导入来覆盖这些包。
autodoc_mock_imports = ['pandas','numpy','scipy','annoy','packaging','scipy.spatial','scipy.sparse','sklearn','sklearn.neighbors','sklearn.linear_model','umap','umap.umap_']
然而，尽管如此，我似乎在构建 ReadTheDocs 端时遇到了问题。似乎尽管被要求模拟 sklearn，但它正在尝试安装它但失败了。
Installed /home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/bbknn-1.4.0-py3.7.egg
Processing dependencies for bbknn==1.4.0
Searching for scikit-learn
Reading https://pypi.org/simple/scikit-learn/
Downloading https://files.pythonhosted.org/packages/db/e2/9c0bde5f81394b627f623557690536b12017b84988a4a1f98ec826edab9e/scikit-learn-0.24.0.tar.gz#sha256=076369634ee72b5a5941440661e2f306ff4ac30903802dc52031c7e9199ac640
Best match: scikit-learn 0.24.0
Processing scikit-learn-0.24.0.tar.gz
Writing /tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.cfg
Running scikit-learn-0.24.0/setup.py -q bdist_egg --dist-dir /tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/egg-dist-tmp-mfl2n2vi
Partial import of sklearn during the build process.
Traceback (most recent call last):
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 201, in check_package_status
module = importlib.import_module(package)
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
File "<frozen importlib._bootstrap>", line 983, in _find_and_load
File "<frozen importlib._bootstrap>", line 965, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'numpy'
Traceback (most recent call last):
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 154, in save_modules
yield saved
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 195, in setup_context
yield
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 250, in run_setup
_execfile(setup_script, ns)
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 45, in _execfile
exec(code, globals, locals)
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 306, in <module>
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 292, in setup_package
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 227, in check_package_status
ImportError: numpy is not installed.
scikit-learn requires numpy >= 1.13.3.
Installation instructions are available on the scikit-learn website: http://scikit-learn.org/stable/install.html
为什么会这样？这可能与我在 setup.py 中要求依赖项的方式有关，它以某种方式绕过了模拟？
install_requires=['Cython','numpy','scipy','annoy','umap-learn','scikit-learn','packaging'],
我通过从 install_requires 中删除 umap-learn 和 scikit-learn 来修复生成了一个文档字符串，但这不是一个理想的解决方案。有人有什么东西吗？
根据一位乐于助人的用户的反馈，我最终得出了一个不那么棘手的解决方案。不幸的是，由于一个无用的用户回复了 pip install -U numpy，讨论就擅离职守了，他等着我弄清楚，编辑了他们的答案并要求我接受它。被拒绝后，答案和评论线程消失了。我什至不记得你的名字，有用的用户，所以我不能把小费归功于你。
显然 ReadTheDocs 使用旧 pip，并且要求 pip>=19.0 使得 scikit-learn 无法从源安装。因此，我将该行添加到 docs/requirements.txt，我之前将其设置为 ReadTheDocs 需求文件。这带来了一些进展——现在不是 scikit-learn 抱怨 numpy，而是 numba。仍然，一些突触连接，我只是处理了通过docs/requirements.txt引起的任何依赖问题，其最终内容是：
pip>=19.0
numpy
llvmlite==0.35.0
这让设置清除。但是，仅仅因为设置已清除，并不意味着 autodoc_mock_imports 可以出于任何原因被剥离。不知道这是为什么。
因此，来自 OP 的快速而肮脏的解决方案可能是解决此问题的最简单方法，其中您只需从 setup.py 的 install_requires 中删除内容。但是，如果您想要让它变得更干净，并且不需要专门的非功能性提交来构建文档，那么拥有一个 ReadTheDocs 需求文件并通过它安装 numpy 可能会解决很多问题。不知道为什么 llvmlite 也这么挑剔，并且在需求文件中以某种方式工作，但在其他情况下却没有，但最终还是到了那里。
我有一个我之前在 ReadTheDocs 上成功构建的包，但现在不再是这样了。我的导入如下：
import pandas as pd
import numpy as np
import scipy
import sys
from annoy import AnnoyIndex
from packaging import version
from scipy.spatial import cKDTree
from scipy.sparse import coo_matrix
from umap.umap_ import fuzzy_simplicial_set
from sklearn.neighbors import KDTree
from sklearn.neighbors import DistanceMetric
from sklearn.linear_model import Ridge
我通过在 Sphinx 中模拟导入来覆盖这些包。
autodoc_mock_imports = ['pandas','numpy','scipy','annoy','packaging','scipy.spatial','scipy.sparse','sklearn','sklearn.neighbors','sklearn.linear_model','umap','umap.umap_']
然而，尽管如此，我似乎在构建 ReadTheDocs 端时遇到了问题。似乎尽管被要求模拟 sklearn，但它正在尝试安装它但失败了。
Installed /home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/bbknn-1.4.0-py3.7.egg
Processing dependencies for bbknn==1.4.0
Searching for scikit-learn
Reading https://pypi.org/simple/scikit-learn/
Downloading https://files.pythonhosted.org/packages/db/e2/9c0bde5f81394b627f623557690536b12017b84988a4a1f98ec826edab9e/scikit-learn-0.24.0.tar.gz#sha256=076369634ee72b5a5941440661e2f306ff4ac30903802dc52031c7e9199ac640
Best match: scikit-learn 0.24.0
Processing scikit-learn-0.24.0.tar.gz
Writing /tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.cfg
Running scikit-learn-0.24.0/setup.py -q bdist_egg --dist-dir /tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/egg-dist-tmp-mfl2n2vi
Partial import of sklearn during the build process.
Traceback (most recent call last):
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 201, in check_package_status
module = importlib.import_module(package)
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
File "<frozen importlib._bootstrap>", line 983, in _find_and_load
File "<frozen importlib._bootstrap>", line 965, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'numpy'
Traceback (most recent call last):
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 154, in save_modules
yield saved
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 195, in setup_context
yield
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 250, in run_setup
_execfile(setup_script, ns)
File "/home/docs/checkouts/readthedocs.org/user_builds/bbknn/envs/latest/lib/python3.7/site-packages/setuptools/sandbox.py", line 45, in _execfile
exec(code, globals, locals)
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 306, in <module>
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 292, in setup_package
File "/tmp/easy_install-1f85jnk0/scikit-learn-0.24.0/setup.py", line 227, in check_package_status
ImportError: numpy is not installed.
scikit-learn requires numpy >= 1.13.3.
Installation instructions are available on the scikit-learn website: http://scikit-learn.org/stable/install.html
为什么会这样？这可能与我在 setup.py 中要求依赖项的方式有关，它以某种方式绕过了模拟？
install_requires=['Cython','numpy','scipy','annoy','umap-learn','scikit-learn','packaging'],
我通过从 install_requires 中删除 umap-learn 和 scikit-learn 来修复生成了一个文档字符串，但这不是一个理想的解决方案。有人有什么东西吗？
根据一位乐于助人的用户的反馈，我最终得出了一个不那么棘手的解决方案。不幸的是，由于一个无用的用户回复了 pip install -U numpy，讨论就擅离职守了，他等着我弄清楚，编辑了他们的答案并要求我接受它。被拒绝后，答案和评论线程消失了。我什至不记得你的名字，有用的用户，所以我不能把小费归功于你。
显然 ReadTheDocs 使用旧 pip，并且要求 pip>=19.0 使得 scikit-learn 无法从源安装。因此，我将该行添加到 docs/requirements.txt，我之前将其设置为 ReadTheDocs 需求文件。这带来了一些进展——现在不是 scikit-learn 抱怨 numpy，而是 numba。仍然，一些突触连接，我只是处理了通过docs/requirements.txt引起的任何依赖问题，其最终内容是：
pip>=19.0
numpy
llvmlite==0.35.0
这让设置清除。但是，仅仅因为设置已清除，并不意味着 autodoc_mock_imports 可以出于任何原因被剥离。不知道这是为什么。
因此，来自 OP 的快速而肮脏的解决方案可能是解决此问题的最简单方法，其中您只需从 setup.py 的 install_requires 中删除内容。但是，如果您想要让它变得更干净，并且不需要专门的非功能性提交来构建文档，那么拥有一个 ReadTheDocs 需求文件并通过它安装 numpy 可能会解决很多问题。不知道为什么 llvmlite 也这么挑剔，并且在需求文件中以某种方式工作，但在其他情况下却没有，但最终还是到了那里。