title: Django segmentation fault while running in docker
body: <p>We are getting segmentation fault while running the application in docker</p>
  
  <pre><code>/path/condapy/envs/env_name/bin/python -vvvvvv manage.py runserver
  
  
  # code object from 
  '/path/condapy/envs/env_name/lib/python3.6/site-packages/django/core/__pycache__/wsgi.cpython-36.pyc'
  import 'django.core.wsgi' # &lt;_frozen_importlib_external.SourceFileLoader object at 0x7f1919dd5a90&gt;
  import 'django.core.servers.basehttp' # &lt;_frozen_importlib_external.SourceFileLoader object at 0x7f1919dca240&gt;
  import 'django.core.management.commands.runserver' # &lt;_frozen_importlib_external.SourceFileLoader object at 0x7f1919dbf630&gt;
  import 'django.contrib.staticfiles.management.commands.runserver' # &lt;_frozen_importlib_external.SourceFileLoader object at 0x7f1919db34a8&gt;
  PyThreadState_Clear: warning: thread still has a frame
  Running in local mode
  Performing system checks...
  
  Segmentation fault
  </code></pre>
  
  <p>Dockerfile</p>
  
  <pre><code>FROM centos:latest
  
  ENV JAVA_VERSON=1.8.0 \
      JAVA_HOME=/usr/lib/jvm/java \
      codepath=&lt;&gt;
  
  RUN yum install -y epel-release cmake wget git python-setuptools zlib-devel openssl-devel python-devel gcc-c++ snappy-devel gcc curl bzip2 java-$JAVA_VERSON-openjdk java-$JAVA_VERSON-openjdk-devel &amp;&amp; \
      yum install -y nginx &amp;&amp; \
      easy_install supervisor &amp;&amp; \
      yum clean all &amp;&amp; \
      rm -rf /etc/localtime &amp;&amp; \
      ln -s /usr/share/zoneinfo/Asia/Kolkata /etc/localtime &amp;&amp; \
      mkdir -p  /logs 
  
  RUN mkdir -p /path/condapy &amp;&amp; \
      curl -sSL https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -o /srv/miniconda.sh &amp;&amp; \
      bash /srv/miniconda.sh -bfp /path/condapy &amp;&amp; \
      /path/condapy/bin/conda install -y python=3 &amp;&amp; \
      /path/condapy/bin/conda update conda &amp;&amp; \
      /path/condapy/bin/conda clean --all --yes
  
  EXPOSE 80
  
  WORKDIR /app_path
  
  ARG aws_access_key_id
  ARG aws_secret_access_key
  ARG env
  
  COPY ./conda_environment.yml /app_path/conda_environment.yml
  
  RUN /path/condapy/bin/conda config --add channels conda-forge &amp;&amp; \
      /path/condapy/bin/conda env create -f=/app_path/conda_environment.yml -n chatty &amp;&amp; \
      rm -rf /opt/conda/pkgs/*
  
  COPY ./ $codepath
  
  CMD ["/usr/bin/supervisord", "-n"]
  </code></pre>
  
  <p>DB config looks good and we have already assigned sufficient memory. Any suggestions?</p>