在我的gitlab-ci.yml中,我使用pandas scikit和scipy测试了一些代码。 构建/管道中的大部分时间都花在编译numpy,scipy上,......
我是否可以创建一个轮子并使用ADD来复制和pip安装已经制作的轮子?
我为最新版本的pip
::
$ cat requirements/base.txt
pip>=8.1.2
setuptools>=20.7.0
wheel>=0.29
numpy
scipy
scikit-learn
这里我的.gitlab-ci
并且每次都有效地花费了很多时间:
$ cat .gitlab-ci
image : python:2
test:
script:
- apt-get update -qy
- apt-get install -y python-dev python-pip python-virtualenv
- pip install -r requirements/base.txt
- ...
尝试回答@ ev-br这里的gitlab-ci管道输出,你可以看到pandas不是一个轮子而是 pandas-0.19.1.tar.gz :
$ pip install -r requirements.txt --cache-dir=/cache
Requirement already satisfied: pip>=9 in /usr/local/lib/python3.6/site-packages (from -r requirements.txt (line 1))
Requirement already satisfied: setuptools>=26 in /usr/local/lib/python3.6/site-packages (from -r requirements.txt (line 2))
Collecting wheel>=0.29 (from -r requirements.txt (line 3))
Using cached wheel-0.29.0-py2.py3-none-any.whl
Collecting setuptools_scm (from -r requirements.txt (line 4))
Using cached setuptools_scm-1.15.0-py2.py3-none-any.whl
Collecting setuptools_scm_git_archive (from -r requirements.txt (line 5))
Using cached setuptools_scm_git_archive-1.0-py2.py3-none-any.whl
Collecting pandas==0.19.1 (from -r requirements.txt (line 6))
Downloading pandas-0.19.1.tar.gz (8.4MB)
Collecting python-dateutil>=2 (from pandas==0.19.1->-r requirements.txt (line 6))
Using cached python_dateutil-2.6.0-py2.py3-none-any.whl
答案 0 :(得分:0)
如果您的点数最近(版本8或更高版本IIRC),您可以通过pip install
numpy和scipy自动使用manulinux车轮。在CI上尝试pip install --upgrade pip
或类似内容。