Why does it take ages to install Pandas on Alpine Linux : <p>I've noticed that installing Pandas and Numpy (it's dependency) in a Docker container using the base OS Alpine vs. CentOS or Debian takes much longer. I created a little test below to demonstrate the time difference. Aside from the few seconds Alpine takes to update and download the build dependencies to install Pandas and Numpy, why does the setup.py take around 70x more time than on Debian install?</p>

<p>Is there any way to speed up the install using Alpine as the base image or is there another base image of comparable size to Alpine that is better to use for packages like Pandas and Numpy?</p>

<p><strong>Dockerfile.debian</strong></p>

<pre><code>FROM python:3.6.4-slim-jessie

RUN pip install pandas
</code></pre>

<p><strong>Build Debian image with Pandas &amp; Numpy:</strong></p>

<pre><code>[PandasDockerTest] time docker build -t debian-pandas -f Dockerfile.debian . --no-cache
    Sending build context to Docker daemon  3.072kB
    Step 1/2 : FROM python:3.6.4-slim-jessie
     ---&gt; 43431c5410f3
    Step 2/2 : RUN pip install pandas
     ---&gt; Running in 2e4c030f8051
    Collecting pandas
      Downloading pandas-0.22.0-cp36-cp36m-manylinux1_x86_64.whl (26.2MB)
    Collecting numpy&gt;=1.9.0 (from pandas)
      Downloading numpy-1.14.1-cp36-cp36m-manylinux1_x86_64.whl (12.2MB)
    Collecting pytz&gt;=2011k (from pandas)
      Downloading pytz-2018.3-py2.py3-none-any.whl (509kB)
    Collecting python-dateutil&gt;=2 (from pandas)
      Downloading python_dateutil-2.6.1-py2.py3-none-any.whl (194kB)
    Collecting six&gt;=1.5 (from python-dateutil&gt;=2-&gt;pandas)
      Downloading six-1.11.0-py2.py3-none-any.whl
    Installing collected packages: numpy, pytz, six, python-dateutil, pandas
    Successfully installed numpy-1.14.1 pandas-0.22.0 python-dateutil-2.6.1 pytz-2018.3 six-1.11.0
    Removing intermediate container 2e4c030f8051
     ---&gt; a71e1c314897
    Successfully built a71e1c314897
    Successfully tagged debian-pandas:latest
    docker build -t debian-pandas -f Dockerfile.debian . --no-cache  0.07s user 0.06s system 0% cpu 13.605 total
</code></pre>

<p><strong>Dockerfile.alpine</strong></p>

<pre><code>FROM python:3.6.4-alpine3.7

RUN apk --update add --no-cache g++

RUN pip install pandas
</code></pre>

<p><strong>Build Alpine image with Pandas &amp; Numpy:</strong></p>

<pre><code>[PandasDockerTest] time docker build -t alpine-pandas -f Dockerfile.alpine . --no-cache
Sending build context to Docker daemon   16.9kB
Step 1/3 : FROM python:3.6.4-alpine3.7
 ---&gt; 4b00a94b6f26
Step 2/3 : RUN apk --update add --no-cache g++
 ---&gt; Running in 4b0c32551e3f
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/main/x86_64/APKINDEX.tar.gz
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/main/x86_64/APKINDEX.tar.gz
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/community/x86_64/APKINDEX.tar.gz
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/community/x86_64/APKINDEX.tar.gz
(1/17) Upgrading musl (1.1.18-r2 -&gt; 1.1.18-r3)
(2/17) Installing libgcc (6.4.0-r5)
(3/17) Installing libstdc++ (6.4.0-r5)
(4/17) Installing binutils-libs (2.28-r3)
(5/17) Installing binutils (2.28-r3)
(6/17) Installing gmp (6.1.2-r1)
(7/17) Installing isl (0.18-r0)
(8/17) Installing libgomp (6.4.0-r5)
(9/17) Installing libatomic (6.4.0-r5)
(10/17) Installing pkgconf (1.3.10-r0)
(11/17) Installing mpfr3 (3.1.5-r1)
(12/17) Installing mpc1 (1.0.3-r1)
(13/17) Installing gcc (6.4.0-r5)
(14/17) Installing musl-dev (1.1.18-r3)
(15/17) Installing libc-dev (0.7.1-r0)
(16/17) Installing g++ (6.4.0-r5)
(17/17) Upgrading musl-utils (1.1.18-r2 -&gt; 1.1.18-r3)
Executing busybox-1.27.2-r7.trigger
OK: 184 MiB in 50 packages
Removing intermediate container 4b0c32551e3f
 ---&gt; be26c3bf4e42
Step 3/3 : RUN pip install pandas
 ---&gt; Running in 36f6024e5e2d
Collecting pandas
  Downloading pandas-0.22.0.tar.gz (11.3MB)
Collecting python-dateutil&gt;=2 (from pandas)
  Downloading python_dateutil-2.6.1-py2.py3-none-any.whl (194kB)
Collecting pytz&gt;=2011k (from pandas)
  Downloading pytz-2018.3-py2.py3-none-any.whl (509kB)
Collecting numpy&gt;=1.9.0 (from pandas)
  Downloading numpy-1.14.1.zip (4.9MB)
Collecting six&gt;=1.5 (from python-dateutil&gt;=2-&gt;pandas)
  Downloading six-1.11.0-py2.py3-none-any.whl
Building wheels for collected packages: pandas, numpy
  Running setup.py bdist_wheel for pandas: started
  Running setup.py bdist_wheel for pandas: still running...
  Running setup.py bdist_wheel for pandas: still running...
  Running setup.py bdist_wheel for pandas: still running...
  Running setup.py bdist_wheel for pandas: still running...
  Running setup.py bdist_wheel for pandas: still running...
  Running setup.py bdist_wheel for pandas: still running...
  Running setup.py bdist_wheel for pandas: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/e8/ed/46/0596b51014f3cc49259e52dff9824e1c6fe352048a2656fc92
  Running setup.py bdist_wheel for numpy: started
  Running setup.py bdist_wheel for numpy: still running...
  Running setup.py bdist_wheel for numpy: still running...
  Running setup.py bdist_wheel for numpy: still running...
  Running setup.py bdist_wheel for numpy: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/9d/cd/e1/4d418b16ea662e512349ef193ed9d9ff473af715110798c984
Successfully built pandas numpy
Installing collected packages: six, python-dateutil, pytz, numpy, pandas
Successfully installed numpy-1.14.1 pandas-0.22.0 python-dateutil-2.6.1 pytz-2018.3 six-1.11.0
Removing intermediate container 36f6024e5e2d
 ---&gt; a93c59e6a106
Successfully built a93c59e6a106
Successfully tagged alpine-pandas:latest
docker build -t alpine-pandas -f Dockerfile.alpine . --no-cache  0.54s user 0.33s system 0% cpu 16:08.47 total
</code></pre>
